_ registry / mcp streamable-http · checked 1h ago

agingresearch-news

https://agingresearch.news

Registry code: db2c17fc7bc7d644

api record

AgingResearch.News (ARN) reads new papers from PubMed, bioRxiv, medRxiv, arXiv and other sources and judges what each paper's own work shows about human aging. Use these tools for questions about aging and longevity research: papers, ARN's stories about them, the drugs, genes, processes and diseases they study, clinical trials and industry news.

Lists hold the papers ARN judged relevant to aging unless you pass min_relevance (0 returns everything it read). Every paper names its study type (human trial, human observational, animal, cells, in silico, review and others): keep animal and cell…

endpoint
https://agingresearch.news/api/mcp
protocol
streamable-http ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is agingresearch-news live?
Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.
Is agingresearch-news free to use?
Yes — the hub reached it with no key and no payment.
What tools does agingresearch-news have?
26 tools: list_papers, get_paper, get_entity, list_claims, list_trials, get_trial, list_news, list_grants, ….
Is agingresearch-news safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
100%

90 days 100%· all time 100%

latency
348ms

last good check

priced tools
0

of 26 tools

_ answered our checks, 90 days 1 checks · signed record
  • unknown → live
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 26 tools
3 open 23 never probed 3 of 26 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • count_pipeline open 1h ago

    Use this when the user asks how many drug and therapy programmes there are, or how a field's pipeline splits. Counts programmes grouped by stage, modality, target, hallmark, indication, the developer's country or the developer, with each group's count at each stage. Takes list_assets' filters: by=target with indication=obesity counts the targets of obesity programmes. An account whose plan includes drug and therapy programmes reads every record in full; any other caller reads the outline AgingResearch.News shows on its asset pages.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "q": {
      "type": "string",
      "examples": [
        "UBX1325"
      ],
      "maxLength": 200,
      "description": "Letters and digits in any of the asset's names or code names (`UBX1325` matches UBX-1325)."
    },
    "by": {
      "enum": [
        "stage",
        "modality",
        "target",
        "hallmark",
        "indication",
        "country",
        "developer"
      ],
      "type": "string",
      "default": "stage",
      "examples": [
        "modality"
      ],
      "description": "What to group by."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "stage": {
      "enum": [
        "approved",
        "phase3",
        "phase2",
        "phase1",
        "human_trials",
        "veterinary",
        "preclinical",
        "discontinued"
      ],
      "type": "string",
      "examples": [
        "phase2"
      ],
      "description": "Stage: with `indication`, the stage for that indication; otherwise the asset's furthest stage."
    },
    "target": {
      "type": "string",
      "examples": [
        "GLP1R"
      ],
      "maxLength": 100,
      "description": "A target: a gene symbol or key (`GLP1R`, `bcl2l1`) or a process key (`mtor`, `cellular-senescence`)."
    },
    "country": {
      "type": "string",
      "pattern": "^[A-Za-z]{2}$",
      "examples": [
        "US"
      ],
      "description": "The developer's country, ISO 3166 alpha-2 (`US`, `GB`, `CH`)."
    },
    "hallmark": {
      "enum": [
        "genomic-instability",
        "telomere-attrition",
        "epigenetic-alterations",
        "loss-of-proteostasis",
        "disabled-macroautophagy",
        "deregulated-nutrient-sensing",
        "mitochondrial-dysfunction",
        "cellular-senescence",
        "stem-cell-exhaustion",
        "altered-intercellular-communication",
        "chronic-inflammation",
        "dysbiosis"
      ],
      "type": "string",
      "examples": [
        "cellular-senescence"
      ],
      "description": "A hallmark of aging the asset acts on."
    },
    "modality": {
      "enum": [
        "small_molecule",
        "antibody",
        "protein",
        "peptide",
        "oligonucleotide",
        "mrna",
        "gene_therapy",
        "gene_editing",
        "cell_therapy",
        "vaccine",
        "microbiome",
        "blood_product",
        "device",
        "supplement",
        "other"
      ],
      "type": "string",
      "examples": [
        "small_molecule"
      ],
      "description": "The kind of therapy (see `modality`)."
    },
    "mechanism": {
      "type": "string",
      "examples": [
        "senescent"
      ],
      "maxLength": 200,
      "description": "Words that must all appear in the asset's mechanism line (case-insensitive)."
    },
    "indication": {
      "type": "string",
      "examples": [
        "alzheimer disease"
      ],
      "maxLength": 200,
      "description": "A disease, by name or entity key (`idiopathic pulmonary fibrosis`, `alzheimer-disease`)."
    },
    "organisation": {
      "type": "string",
      "examples": [
        "unity-biotechnology"
      ],
      "maxLength": 200,
      "description": "An organisation key: the assets it develops, partners on or licensed out."
    }
  },
  "additionalProperties": false
}
    arguments 141 lines
  • list_conferences open 1h ago

    Use this when the user asks which meetings on aging research and age-related disease are coming up, or which have just been held. The conference calendar: meetings still to come or on, soonest first, then recent ones, each edition with its dates, place and how many of its abstracts ARN holds. Read one, and an edition's abstracts, with get_conference.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {},
  "additionalProperties": false
}
    arguments 6 lines
  • find_entities open 1h ago

    Use this to find the type and key of what a question names (a drug, supplement or diet, a gene or protein, a biological process, a disease, a biomarker, an organism, a method or a hallmark of aging) before get_entity, list_claims or list_grants. Matches part of a name, a key or a known synonym, case-insensitive, most-studied first, with how many of ARN's papers involve each. Pass a result's type and key to get_entity.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "q": {
      "type": "string",
      "examples": [
        "rapa"
      ],
      "maxLength": 100,
      "description": "Match on name or key, case-insensitive substring."
    },
    "type": {
      "type": "string",
      "pattern": "^[a-z_]{1,32}$",
      "examples": [
        "intervention"
      ],
      "description": "Entity type, e.g. intervention, gene, pathway, component, system, method, hallmark, phenotype, organism, tissue, disease, biomarker, mesh."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    }
  },
  "additionalProperties": false
}
    arguments 35 lines
  • list_papers unknown never probed

    Use this when the user asks what is new: the latest papers in a field (mitochondrial dysfunction, immune aging, senolytics), of a study type such as randomised trials, on a body system, or by one author (author takes a name, or an author_id from get_paper), for example to shortlist a lab's journal club. Lists the newest papers ARN has read, by the date they entered ARN, with the same filters as search_papers and an optional words filter. For the papers that best answer a question, use search_papers.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "q": {
      "type": "string",
      "examples": [
        "rapamycin"
      ],
      "maxLength": 200,
      "description": "Full-text filter over title and abstract. Supports \"quoted phrases\", OR and -exclusions. Results stay in date order; use search_papers for ranked results."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "since": {
      "type": "string",
      "format": "date",
      "examples": [
        "2026-09-28"
      ],
      "description": "Only papers that entered ARN on or after this UTC date (YYYY-MM-DD; a full ISO timestamp is cut to its date)."
    },
    "until": {
      "type": "string",
      "format": "date",
      "description": "Only papers that entered ARN on or before this UTC date (YYYY-MM-DD)."
    },
    "author": {
      "type": "string",
      "examples": [
        "David Sinclair"
      ],
      "maxLength": 80,
      "description": "Papers by an author. A name matches every author who answers to it: the words in any order, with or without accents, an initial standing for any name it begins (`sinclair d`). An `author_id` from a paper's `authors_full` (an OpenAlex author id such as `A5022713595`, or an ORCID iD) matches that one person."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "system": {
      "type": "array",
      "items": {
        "enum": [
          "eye",
          "ear",
          "heart-vessels",
          "kidney",
          "lung",
          "reproductive",
          "skin",
          "brain-nerves",
          "blood-immune",
          "bone-joints",
          "muscle",
          "metabolism",
          "gut-microbiome",
          "whole-body"
        ],
        "type": "string"
      },
      "examples": [
        [
          "brain-nerves",
          "muscle"
        ]
      ],
      "minItems": 1,
      "description": "Body system key (see `systems`). A paper matches when it involves any of them. Only papers that have been through extraction have systems."
    },
    "age_link": {
      "type": "array",
      "items": {
        "enum": [
          "lifespan_healthspan",
          "aged_comparison",
          "age_trajectory",
          "aging_outcome",
          "age_accumulating_state",
          "aging_lever",
          "prevention",
          "tool_or_field",
          "rejuvenation_tech",
          "population_only",
          "asserted_only",
          "none"
        ],
        "type": "string"
      },
      "examples": [
        [
          "lifespan_healthspan",
          "aging_lever"
        ]
      ],
      "minItems": 1,
      "description": "How the work itself connects to aging (see `judgement.age_link`)."
    },
    "category": {
      "type": "array",
      "items": {
        "enum": [
          "mechanisms",
          "interventions",
          "biomarkers",
          "populations",
          "ai-data",
          "industry-policy"
        ],
        "type": "string"
      },
      "examples": [
        [
          "interventions"
        ]
      ],
      "minItems": 1,
      "description": "Category slug. A paper matches when its category or its secondary category is listed."
    },
    "preprint": {
      "type": "boolean",
      "description": "`true` for preprints only, `false` for peer-reviewed papers only. Omit for both."
    },
    "study_type": {
      "type": "array",
      "items": {
        "enum": [
          "human_trial",
          "human_observational",
          "animal",
          "invertebrate",
          "cells",
          "computational",
          "review",
          "other"
        ],
        "type": "string"
      },
      "examples": [
        [
          "human_trial",
          "animal"
        ]
      ],
      "minItems": 1,
      "description": "Main source of evidence."
    },
    "min_relevance": {
      "type": "number",
      "maximum": 3,
      "minimum": 0,
      "description": "Lowest aging-relevance score to include (0 to 3, see `judgement.relevance`). Without it, the papers the site shows; 1 adds tangential papers; 0 returns every paper ARN read, most of which are not about aging."
    }
  },
  "additionalProperties": false
}
    arguments 161 lines
  • get_paper unknown never probed

    Use this when the user wants one paper in depth: what it did and found, in which species and how many subjects, its caveats, who wrote it and where they work. Takes an ARN paper id such as MED-42823970 from another tool's results. Returns ARN's judgement of it, the language it was published in with its own-language title when that is not English, every author with ORCID iD and institutions, ARN's full story (headline, body, why it matters, caveats) when published, the entities and findings extracted from it, and a link to the paper at its source. ARN's reading starts from the paper's record and abstract; it does not replace the paper.

    mcp-tool

    {
  "type": "object",
  "required": [
    "id"
  ],
  "properties": {
    "id": {
      "type": "string",
      "examples": [
        "MED-42823970"
      ],
      "maxLength": 80,
      "description": "ARN paper id, e.g. MED-42823970."
    }
  },
  "additionalProperties": false
}
    arguments 17 lines
  • get_entity unknown never probed

    Use this for questions about one drug, supplement, gene, process or disease, such as: is there human evidence for this intervention; has the finding been replicated by independent labs; in which species; what trials test it and how many have posted no results; who funds the work and which companies are tied to it; what the newest papers on it report. Takes a type and key from find_entities (intervention rapamycin, disease sarcopenia); a synonym or an old key answers with the entity it now names. Returns the entity with the papers that involve it, newest first, and the role it plays in each. For an intervention, a gene or a process, `evidence` gives its evidence as structure, never as a grade: the species its findings reach and whether independent labs found the same there, the labs and countries behind them, the findings against, its trials and those with no results posted, its funders and its company ties. The counts are of ARN's record, not of all the literature. Not for personal medical advice or doses.

    mcp-tool

    {
  "type": "object",
  "required": [
    "type",
    "key"
  ],
  "properties": {
    "key": {
      "type": "string",
      "examples": [
        "rapamycin"
      ],
      "maxLength": 200,
      "description": "Entity key within its type."
    },
    "type": {
      "type": "string",
      "pattern": "^[a-z_]{1,32}$",
      "examples": [
        "intervention"
      ],
      "description": "Entity type."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "min_relevance": {
      "type": "number",
      "maximum": 3,
      "minimum": 0,
      "description": "Lowest aging-relevance score for the papers listed. Default: no filter."
    }
  },
  "additionalProperties": false
}
    arguments 44 lines
  • list_claims unknown never probed

    Use this when the user asks what has been found about a relation: does an intervention extend lifespan, and in which organisms; what lowers a biomarker; what acts on a process. Lists findings extracted from papers as subject, relation and object (for example rapamycin extends_lifespan in Mus musculus), with organism, conditions, effect size and the paper, newest first. Narrow by subject, object, relation, organism or paper. ARN's models extract the findings from the papers; check one that matters against its paper with get_paper. Not for personal medical advice.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "object": {
      "type": "string",
      "examples": [
        "lifespan"
      ],
      "maxLength": 100,
      "description": "Object text, entity name or entity key (case-insensitive substring)."
    },
    "subject": {
      "type": "string",
      "examples": [
        "rapamycin"
      ],
      "maxLength": 100,
      "description": "Subject text, entity name or entity key (case-insensitive substring)."
    },
    "organism": {
      "type": "string",
      "examples": [
        "mus musculus"
      ],
      "maxLength": 60,
      "description": "Organism, e.g. Homo sapiens, Mus musculus (case-insensitive substring)."
    },
    "paper_id": {
      "type": "string",
      "maxLength": 80,
      "description": "Only claims from this paper."
    },
    "relation": {
      "type": "string",
      "examples": [
        "extends_lifespan"
      ],
      "maxLength": 40,
      "description": "Exact relation, e.g. increases, decreases, associated_with, extends_lifespan."
    }
  },
  "additionalProperties": false
}
    arguments 56 lines
  • list_trials unknown never probed

    Use this when the user asks about clinical trials on aging or an age-related condition: what is recruiting, what changed lately (a new status, a completion, results posted), which trials test a drug, or which companies run them. Lists trials from ClinicalTrials.gov that bear on human aging, newest registry update first: phase, status, sponsor, size, conditions, interventions and the latest change. Narrow by words, phase, recruitment status, focus, industry sponsor or update date. Only the trials ARN judged relevant to aging, not every registered trial. Read one with get_trial.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "q": {
      "type": "string",
      "examples": [
        "rapamycin"
      ],
      "maxLength": 200,
      "description": "Words that must all appear in the trial's titles, conditions, interventions, keywords or sponsor (case-insensitive)."
    },
    "focus": {
      "type": "array",
      "items": {
        "enum": [
          "intervention",
          "condition",
          "endpoint",
          "biomarker",
          "observational",
          "other"
        ],
        "type": "string"
      },
      "examples": [
        [
          "intervention"
        ]
      ],
      "minItems": 1,
      "description": "The trial's main connection to aging (see `focus`)."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "phase": {
      "type": "array",
      "items": {
        "enum": [
          "1",
          "2",
          "3",
          "4",
          "none"
        ],
        "type": "string"
      },
      "examples": [
        [
          "2",
          "3"
        ]
      ],
      "minItems": 1,
      "description": "Phase: `1` (early phase 1 and phase 1), `2`, `3`, `4`, or `none` for studies with no phase."
    },
    "since": {
      "type": "string",
      "format": "date",
      "examples": [
        "2026-09-01"
      ],
      "description": "Only trials the registry updated on or after this date (YYYY-MM-DD)."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "status": {
      "type": "array",
      "items": {
        "enum": [
          "recruiting",
          "active",
          "completed",
          "stopped"
        ],
        "type": "string"
      },
      "examples": [
        [
          "recruiting"
        ]
      ],
      "minItems": 1,
      "description": "Recruitment status: `recruiting` (recruiting, not yet recruiting or by invitation), `active` (active, not recruiting), `completed`, or `stopped` (terminated, withdrawn or suspended)."
    },
    "industry": {
      "type": "boolean",
      "description": "`true` for trials whose lead sponsor is a company, `false` for the rest. Omit for both."
    },
    "min_relevance": {
      "type": "number",
      "maximum": 3,
      "minimum": 0,
      "description": "Lowest aging-relevance score to include (0 to 3, see `relevance`). Default 1.8, the trials /trials shows."
    }
  },
  "additionalProperties": false
}
    arguments 106 lines
  • get_trial unknown never probed

    Use this when the user asks about one clinical trial by its registry number (NCT, ISRCTN, ChiCTR, CTRI, CTIS and the rest): its design, outcomes and dates, what changed and when, and which papers cite it. Returns the registry's summary, outcomes and dates, every change ARN recorded and the papers that cite it. A record from the WHO ICTRP carries its attribution and the day WHO processed it, to show with it.

    mcp-tool

    {
  "type": "object",
  "required": [
    "nct_id"
  ],
  "properties": {
    "nct_id": {
      "type": "string",
      "pattern": "^[A-Za-z][A-Za-z-]{1,12} ?[0-9][0-9A-Za-z-]{3,30}$",
      "examples": [
        "NCT04488601"
      ],
      "description": "The trial's registry number, e.g. NCT04488601 or ISRCTN12345678."
    }
  },
  "additionalProperties": false
}
    arguments 17 lines
  • list_news unknown never probed

    Use this when the user asks about events in aging research and the longevity industry: company financings and deals, trial readouts, approvals and regulators, policy, conferences. One story per event, newest first, in ARN's words with a link to every outlet that covered it. Narrow by words, kind or date. Only news of this field; not for general, political or market news.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "q": {
      "type": "string",
      "examples": [
        "Retro Biosciences"
      ],
      "maxLength": 200,
      "description": "Words that must all appear in the story's headline or summary (case-insensitive)."
    },
    "kind": {
      "enum": [
        "company",
        "trial_result",
        "regulatory",
        "funding",
        "research_news",
        "policy",
        "conference",
        "other"
      ],
      "type": "string",
      "examples": [
        "funding"
      ],
      "description": "Only stories of this kind."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "since": {
      "type": "string",
      "format": "date",
      "examples": [
        "2026-09-28"
      ],
      "description": "Only stories with coverage on or after this UTC date (YYYY-MM-DD)."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    }
  },
  "additionalProperties": false
}
    arguments 52 lines
  • list_grants unknown never probed

    Use this when the user asks who funds work on a target, a drug, a process or a lab, how much and since when, or what a funder pays for in aging research. Lists research grants from NIH, the EU (CORDIS), UKRI and Wellcome that bear on aging, judged for aging as papers are, newest award first: title, funder, holder, investigators, amount, funded period, scheme and a link to the record. Narrow by an entity the title names (type:key, as find_entities gives), a funder or holder key, title words or award date. Other funders and private money are not here; for company financings use list_news.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "q": {
      "type": "string",
      "examples": [
        "senescence"
      ],
      "maxLength": 200,
      "description": "Words of the grant's title (\"quoted phrases\", OR and -exclusions work)."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "since": {
      "type": "string",
      "format": "date",
      "examples": [
        "2026-09-01"
      ],
      "description": "Only grants awarded on or after this date (YYYY-MM-DD)."
    },
    "until": {
      "type": "string",
      "format": "date",
      "description": "Only grants awarded on or before this date (YYYY-MM-DD)."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "entity": {
      "type": "string",
      "pattern": "^[a-z]+:.+$",
      "examples": [
        "intervention:rapamycin"
      ],
      "maxLength": 200,
      "description": "Only grants whose titles name this entity, as `type:key` (see /entities), e.g. `intervention:rapamycin` or `disease:sarcopenia`."
    },
    "funder": {
      "type": "string",
      "examples": [
        "nia"
      ],
      "maxLength": 200,
      "description": "Only grants from this funder, by its organisation key or name, e.g. `nia` or `wellcome`."
    },
    "holder": {
      "type": "string",
      "maxLength": 200,
      "description": "Only grants held by this organisation (its key) or investigator (`person:` and their key), e.g. `buck-institute-for-research-on-aging`."
    }
  },
  "additionalProperties": false
}
    arguments 62 lines
  • get_conference unknown never probed

    Use this when the user asks about one meeting from list_conferences, or what was presented there. Returns its organiser, site and every edition; with `edition`, that edition's abstracts worth reading, the most relevant first, each with its number, format and the paper it was later published as. An abstract is not a peer-reviewed paper. Read one in full with get_paper.

    mcp-tool

    {
  "type": "object",
  "required": [
    "id"
  ],
  "properties": {
    "id": {
      "type": "string",
      "pattern": "^[a-z0-9-]{1,60}$",
      "examples": [
        "gsa"
      ],
      "description": "Conference id from list_conferences, e.g. gsa."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "edition": {
      "type": "string",
      "pattern": "^[a-z0-9-]{1,40}$",
      "examples": [
        "2025"
      ],
      "description": "An edition from `editions`, e.g. 2025: list its abstracts."
    },
    "min_visibility": {
      "enum": [
        "out",
        "matchable",
        "searchable",
        "visible",
        "core"
      ],
      "type": "string",
      "default": "visible",
      "description": "With `edition`: the lowest visibility band of the abstracts listed (see `judgement.visibility`). Default `visible`, the abstracts the site lists."
    }
  },
  "additionalProperties": false
}
    arguments 49 lines
  • list_assets unknown never probed

    Use this when the user asks which drugs or therapies are in development against a target, a mechanism, a hallmark of aging or an age-related disease, who develops them and how far each has got. Lists drug and therapy programmes (assets), furthest stage first: each with its developers and partners, code names, modality, targets, mechanism, indications with the stage of each, hallmarks of aging and lifespan evidence. Narrow by target (a gene symbol such as GLP1R, or a process), mechanism words, modality, hallmark, indication, stage, the developer's country, an organisation or a name. Read one in full with get_asset; count them with count_pipeline. An account whose plan includes drug and therapy programmes reads every record in full; any other caller reads the outline AgingResearch.News shows on its asset pages.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "q": {
      "type": "string",
      "examples": [
        "UBX1325"
      ],
      "maxLength": 200,
      "description": "Letters and digits in any of the asset's names or code names (`UBX1325` matches UBX-1325)."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "stage": {
      "enum": [
        "approved",
        "phase3",
        "phase2",
        "phase1",
        "human_trials",
        "veterinary",
        "preclinical",
        "discontinued"
      ],
      "type": "string",
      "examples": [
        "phase2"
      ],
      "description": "Stage: with `indication`, the stage for that indication; otherwise the asset's furthest stage."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "target": {
      "type": "string",
      "examples": [
        "GLP1R"
      ],
      "maxLength": 100,
      "description": "A target: a gene symbol or key (`GLP1R`, `bcl2l1`) or a process key (`mtor`, `cellular-senescence`)."
    },
    "country": {
      "type": "string",
      "pattern": "^[A-Za-z]{2}$",
      "examples": [
        "US"
      ],
      "description": "The developer's country, ISO 3166 alpha-2 (`US`, `GB`, `CH`)."
    },
    "hallmark": {
      "enum": [
        "genomic-instability",
        "telomere-attrition",
        "epigenetic-alterations",
        "loss-of-proteostasis",
        "disabled-macroautophagy",
        "deregulated-nutrient-sensing",
        "mitochondrial-dysfunction",
        "cellular-senescence",
        "stem-cell-exhaustion",
        "altered-intercellular-communication",
        "chronic-inflammation",
        "dysbiosis"
      ],
      "type": "string",
      "examples": [
        "cellular-senescence"
      ],
      "description": "A hallmark of aging the asset acts on."
    },
    "modality": {
      "enum": [
        "small_molecule",
        "antibody",
        "protein",
        "peptide",
        "oligonucleotide",
        "mrna",
        "gene_therapy",
        "gene_editing",
        "cell_therapy",
        "vaccine",
        "microbiome",
        "blood_product",
        "device",
        "supplement",
        "other"
      ],
      "type": "string",
      "examples": [
        "small_molecule"
      ],
      "description": "The kind of therapy (see `modality`)."
    },
    "mechanism": {
      "type": "string",
      "examples": [
        "senescent"
      ],
      "maxLength": 200,
      "description": "Words that must all appear in the asset's mechanism line (case-insensitive)."
    },
    "indication": {
      "type": "string",
      "examples": [
        "alzheimer disease"
      ],
      "maxLength": 200,
      "description": "A disease, by name or entity key (`idiopathic pulmonary fibrosis`, `alzheimer-disease`)."
    },
    "organisation": {
      "type": "string",
      "examples": [
        "unity-biotechnology"
      ],
      "maxLength": 200,
      "description": "An organisation key: the assets it develops, partners on or licensed out."
    }
  },
  "additionalProperties": false
}
    arguments 129 lines
  • get_asset unknown never probed

    Use this when the user asks about one drug or therapy programme by its name or any code name (ubx1325, UBX-1325, BMS-986278). Returns its developers, partners and licensors, targets, mechanism, modality, every indication with its stage and the trial or source behind it, its lifespan evidence and the news that names it. An account whose plan includes drug and therapy programmes reads every record in full; any other caller reads the outline AgingResearch.News shows on its asset pages.

    mcp-tool

    {
  "type": "object",
  "required": [
    "key"
  ],
  "properties": {
    "key": {
      "type": "string",
      "examples": [
        "ubx1325"
      ],
      "maxLength": 120,
      "description": "The asset's key or a code name."
    }
  },
  "additionalProperties": false
}
    arguments 17 lines
  • follow unknown never probed

    Use this when the user asks to follow a drug, gene, process, disease or other entity on AgingResearch.News, so its new papers reach them. Takes the type and key that find_entities or get_entity give. Following is saved to the user's ARN account: new papers on it appear in For you and the daily follow email.

    mcp-tool

    {
  "type": "object",
  "required": [
    "type",
    "key"
  ],
  "properties": {
    "key": {
      "type": "string",
      "maxLength": 200,
      "minLength": 1,
      "description": "The entity's key within its type, such as rapamycin."
    },
    "type": {
      "enum": [
        "intervention",
        "gene",
        "pathway",
        "disease",
        "biomarker",
        "hallmark",
        "organism",
        "system",
        "component",
        "method"
      ],
      "type": "string",
      "description": "The entity's type, as find_entities or get_entity gives it."
    }
  },
  "additionalProperties": false
}
    arguments 32 lines
  • unfollow unknown never probed

    Use this when the user asks to stop following a drug, gene, process or other entity on AgingResearch.News. Takes the type and key that list_follows, find_entities or get_entity give. Removes the follow from the user's ARN account.

    mcp-tool

    {
  "type": "object",
  "required": [
    "type",
    "key"
  ],
  "properties": {
    "key": {
      "type": "string",
      "maxLength": 200,
      "minLength": 1,
      "description": "The entity's key within its type, such as rapamycin."
    },
    "type": {
      "enum": [
        "intervention",
        "gene",
        "pathway",
        "disease",
        "biomarker",
        "hallmark",
        "organism",
        "system",
        "component",
        "method"
      ],
      "type": "string",
      "description": "The entity's type, as find_entities or get_entity gives it."
    }
  },
  "additionalProperties": false
}
    arguments 32 lines
  • list_follows unknown never probed

    Use this when the user asks what they follow on AgingResearch.News. Lists the drugs, genes, processes and saved searches their ARN account follows, newest first, each with its page on ARN; an entity's id is the type:key that unfollow takes.

    mcp-tool

    {
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
    arguments 5 lines
  • list_questions unknown never probed

    Use this when the user asks about questions they asked AgingResearch.News (Ask) before. Lists their most recent conversations, newest first, each with its title and its address on ARN, where the answer and its sources are.

    mcp-tool

    {
  "type": "object",
  "properties": {
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "How many, 1 to 25."
    }
  },
  "additionalProperties": false
}
    arguments 13 lines
  • open_arn unknown never probed

    Use this when the user asks to open AgingResearch.News or to see their ARN feed, follows and recent questions in one place. Shows the newest stories ARN wrote (For you when the user is signed in, else Top), what they follow and their recent questions, with search.

    mcp-tool

    {
  "type": "object",
  "properties": {
    "tab": {
      "enum": [
        "for-you",
        "top"
      ],
      "type": "string",
      "description": "Which feed to open on."
    }
  },
  "additionalProperties": false
}
    arguments 14 lines
  • list_feed unknown never probed

    The sidebar's feed: For you or Top, as story cards.

    mcp-tool

    {
  "type": "object",
  "properties": {
    "tab": {
      "enum": [
        "for-you",
        "top"
      ],
      "type": "string"
    }
  },
  "additionalProperties": false
}
    arguments 13 lines
  • search_arn unknown never probed

    The sidebar's search: entities and papers matching words, as cards.

    mcp-tool

    {
  "type": "object",
  "required": [
    "q"
  ],
  "properties": {
    "q": {
      "type": "string",
      "maxLength": 100,
      "minLength": 1
    }
  },
  "additionalProperties": false
}
    arguments 14 lines
  • ask_arn unknown never probed

    Use this when the user asks a research question on the biology of aging, longevity interventions, age-related disease, or the people and companies of the field (for example: does rapamycin extend lifespan in people, what is known about senolytics for frailty, who works on epigenetic clocks). Not for personal medical advice, doses or symptoms. ARN answers from its own record: the papers it has judged, each one's design, species, size and findings, its evidence on what the question names (trials, approvals, mouse lifespan results, human genetics), and its records of researchers and companies; it says plainly when that record is thin. Returns an answer of at most about 350 words with numbered sources, each linked to its page on ARN, and the conversation's address. It spends one of the user's Ask questions for the day on their AgingResearch.News account. Pass conversation_id for a follow-up. If the answer takes longer than a call allows, the result says so: read it with get_ask_answer and its question_id.

    mcp-tool

    {
  "type": "object",
  "required": [
    "question"
  ],
  "properties": {
    "question": {
      "type": "string",
      "maxLength": 8000,
      "minLength": 3,
      "description": "The research question in the user's words, in any language; the answer is written in the question's language."
    },
    "conversation_id": {
      "type": "string",
      "pattern": "^[A-Za-z0-9-]{8,64}$",
      "description": "To ask a follow-up in a conversation this tool or ask_arn started: its `conversation.id`. Leave out to start a new conversation."
    }
  },
  "additionalProperties": false
}
    arguments 20 lines
  • start_ultradeep unknown never probed

    Use this when the user asks for a full review of the evidence on a research question in aging or longevity, beyond a short answer. Not for personal medical advice, doses or symptoms. ARN reads up to 32 of its sources on the question and writes, in the next several minutes, a review in five sections: the bottom line, the evidence by kind of study, contradictions and gaps, how far it has got toward patients, and what would change the answer. It is started on the user's own AgingResearch.News account and counts against their plan's Ultradeep reviews. Returns at once with the address of the conversation where the review appears and a question_id: get_ask_answer says where it stands and gives the review once it is in.

    mcp-tool

    {
  "type": "object",
  "required": [
    "question"
  ],
  "properties": {
    "question": {
      "type": "string",
      "maxLength": 8000,
      "minLength": 3,
      "description": "The research question in the user's words, in any language; the answer is written in the question's language."
    },
    "conversation_id": {
      "type": "string",
      "pattern": "^[A-Za-z0-9-]{8,64}$",
      "description": "To ask a follow-up in a conversation this tool or ask_arn started: its `conversation.id`. Leave out to start a new conversation."
    }
  },
  "additionalProperties": false
}
    arguments 20 lines
  • get_ask_answer unknown never probed

    Use this when ask_arn or start_ultradeep said an answer is still being written, or the user wants it again: it reads that question's answer by the question_id they gave: the answer with its numbered sources once it is written, or where it stands while ARN writes it. Waits up to 20 seconds for a short answer that is nearly done; an Ultradeep review takes several minutes.

    mcp-tool

    {
  "type": "object",
  "required": [
    "question_id"
  ],
  "properties": {
    "question_id": {
      "type": "integer",
      "minimum": 1,
      "description": "The question_id ask_arn or start_ultradeep gave."
    }
  },
  "additionalProperties": false
}
    arguments 14 lines
  • search_papers unknown never probed

    Use this when the user asks what research has found on a question in the biology of aging or an age-related disease, often without the word aging: senescence and senolytics, epigenetic clocks, partial reprogramming, mitochondrial dysfunction, NAD+, inflammaging and immune aging, ovarian aging and menopause, neurodegeneration, cardiovascular and metabolic decline, sarcopenia, regeneration, and long-lived species such as naked mole rats and whales. Searches the titles and abstracts of the papers ARN has read, best match first. Supports "quoted phrases", OR and -exclusions; narrow by study type, category, body system, age link, preprint status, author or the date a paper entered ARN. By default only papers ARN judged relevant to aging. Each result gives its study type, ARN's judgement, its subjects and ARN's story when one was published. ARN's record is not all of PubMed: no match does not mean no study exists. Not for personal medical advice, symptoms or product recommendations. Read one in full with get_paper.

    mcp-tool

    {
  "type": "object",
  "required": [
    "q"
  ],
  "properties": {
    "q": {
      "type": "string",
      "examples": [
        "senolytic mice"
      ],
      "maxLength": 200,
      "description": "Search terms. Supports \"quoted phrases\", OR and -exclusions."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "since": {
      "type": "string",
      "format": "date",
      "examples": [
        "2026-09-28"
      ],
      "description": "Only papers that entered ARN on or after this UTC date (YYYY-MM-DD; a full ISO timestamp is cut to its date)."
    },
    "until": {
      "type": "string",
      "format": "date",
      "description": "Only papers that entered ARN on or before this UTC date (YYYY-MM-DD)."
    },
    "author": {
      "type": "string",
      "examples": [
        "David Sinclair"
      ],
      "maxLength": 80,
      "description": "Papers by an author. A name matches every author who answers to it: the words in any order, with or without accents, an initial standing for any name it begins (`sinclair d`). An `author_id` from a paper's `authors_full` (an OpenAlex author id such as `A5022713595`, or an ORCID iD) matches that one person."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "system": {
      "type": "array",
      "items": {
        "enum": [
          "eye",
          "ear",
          "heart-vessels",
          "kidney",
          "lung",
          "reproductive",
          "skin",
          "brain-nerves",
          "blood-immune",
          "bone-joints",
          "muscle",
          "metabolism",
          "gut-microbiome",
          "whole-body"
        ],
        "type": "string"
      },
      "examples": [
        [
          "brain-nerves",
          "muscle"
        ]
      ],
      "minItems": 1,
      "description": "Body system key (see `systems`). A paper matches when it involves any of them. Only papers that have been through extraction have systems."
    },
    "age_link": {
      "type": "array",
      "items": {
        "enum": [
          "lifespan_healthspan",
          "aged_comparison",
          "age_trajectory",
          "aging_outcome",
          "age_accumulating_state",
          "aging_lever",
          "prevention",
          "tool_or_field",
          "rejuvenation_tech",
          "population_only",
          "asserted_only",
          "none"
        ],
        "type": "string"
      },
      "examples": [
        [
          "lifespan_healthspan",
          "aging_lever"
        ]
      ],
      "minItems": 1,
      "description": "How the work itself connects to aging (see `judgement.age_link`)."
    },
    "category": {
      "type": "array",
      "items": {
        "enum": [
          "mechanisms",
          "interventions",
          "biomarkers",
          "populations",
          "ai-data",
          "industry-policy"
        ],
        "type": "string"
      },
      "examples": [
        [
          "interventions"
        ]
      ],
      "minItems": 1,
      "description": "Category slug. A paper matches when its category or its secondary category is listed."
    },
    "preprint": {
      "type": "boolean",
      "description": "`true` for preprints only, `false` for peer-reviewed papers only. Omit for both."
    },
    "study_type": {
      "type": "array",
      "items": {
        "enum": [
          "human_trial",
          "human_observational",
          "animal",
          "invertebrate",
          "cells",
          "computational",
          "review",
          "other"
        ],
        "type": "string"
      },
      "examples": [
        [
          "human_trial",
          "animal"
        ]
      ],
      "minItems": 1,
      "description": "Main source of evidence."
    },
    "min_relevance": {
      "type": "number",
      "maximum": 3,
      "minimum": 0,
      "description": "Lowest aging-relevance score to include (0 to 3, see `judgement.relevance`). Without it, the papers the site shows; 1 adds tangential papers; 0 returns every paper ARN read, most of which are not about aging."
    }
  },
  "additionalProperties": false
}
    arguments 163 lines
  • list_stories unknown never probed

    Use this when the user wants a readable round-up of recent findings: what happened this week in aging research, the notable results in a field, or a short list for a journal club. Lists the stories ARN wrote about new papers, newest first, each checked against its paper: a plain-language headline, body, why it matters and caveats, with the paper. Narrow by category, body system, study type or publication date. Only the papers ARN chose to write about; for every paper on a question use search_papers.

    mcp-tool

    {
  "type": "object",
  "required": [],
  "properties": {
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Results per page, 1 to 25."
    },
    "since": {
      "type": "string",
      "format": "date",
      "examples": [
        "2026-09-28"
      ],
      "description": "Only stories published on or after this UTC date (YYYY-MM-DD)."
    },
    "until": {
      "type": "string",
      "format": "date",
      "description": "Only stories published on or before this UTC date (YYYY-MM-DD)."
    },
    "cursor": {
      "type": "string",
      "maxLength": 400,
      "description": "Opaque cursor from `pagination.next_cursor` of the previous page. Keep the other parameters the same."
    },
    "system": {
      "type": "array",
      "items": {
        "enum": [
          "eye",
          "ear",
          "heart-vessels",
          "kidney",
          "lung",
          "reproductive",
          "skin",
          "brain-nerves",
          "blood-immune",
          "bone-joints",
          "muscle",
          "metabolism",
          "gut-microbiome",
          "whole-body"
        ],
        "type": "string"
      },
      "examples": [
        [
          "brain-nerves",
          "muscle"
        ]
      ],
      "minItems": 1,
      "description": "Body system key (see `systems`). A paper matches when it involves any of them. Only papers that have been through extraction have systems."
    },
    "category": {
      "type": "array",
      "items": {
        "enum": [
          "mechanisms",
          "interventions",
          "biomarkers",
          "populations",
          "ai-data",
          "industry-policy"
        ],
        "type": "string"
      },
      "examples": [
        [
          "interventions"
        ]
      ],
      "minItems": 1,
      "description": "Category slug. A paper matches when its category or its secondary category is listed."
    },
    "study_type": {
      "type": "array",
      "items": {
        "enum": [
          "human_trial",
          "human_observational",
          "animal",
          "invertebrate",
          "cells",
          "computational",
          "review",
          "other"
        ],
        "type": "string"
      },
      "examples": [
        [
          "human_trial",
          "animal"
        ]
      ],
      "minItems": 1,
      "description": "Main source of evidence."
    }
  },
  "additionalProperties": false
}
    arguments 107 lines
_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ is this your agent? claim it: badge, payouts, history

Nobody has claimed this listing. Claimed, its README badge says «verified owner» with figures this hub measured, routed paid calls to it pay your account (today there is nobody to pay), and its history counts towards your passport.

  1. Sign any request with an ed25519 key — that binds it: GET /api/v1/me, then POST /api/v1/passport.
  2. Prove it is yours. Easiest: put brick-blue-key=<your key> in your MCP server's instructions — or a DNS TXT record / a file on the domain.
  3. Ask the hub to check: POST /api/v1/passport/claim-endpoint with this listing's id db2c17fc7bc7d644.

Every step, filled in for this listing: https://brick.blue/api/v1/agents/db2c17fc7bc7d644/claim. Over MCP: the claim_endpoint tool.

_ for your README measured, not declared

measured by brick.blue

[![measured by brick.blue](https://brick.blue/api/v1/agents/db2c17fc7bc7d644/badge.svg)](https://brick.blue/agent/db2c17fc7bc7d644?ref=badge)

The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.

_ how we know
card completeness
100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
ok
0
failed
0
success rate
—
median latency
—
work
attempts
0
accepted
0
rejected
0
acceptance rate
—
settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
—
reviews
paid reviews
0
positive
0
negative
0
score
—

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.