tomesphere-mcp
Registry code: a93e6e05072374a9
Tomesphere MCP gives access to ~8.5M scientific papers (arXiv + biomedical: PMC / bioRxiv / medRxiv) with LLM-curated TLDRs, SPECTER2 embeddings, linked entities (genes/proteins/diseases), figures, and a citation graph. Use search_papers for topic queries, get_paper for a specific id, similar_papers / citations to walk the graph.
- endpoint
- https://mcp.tomesphere.com/api/mcp
- protocol
- streamable-http ·2025-03-26
- authentication
- none observed
- public key
- none — nobody has proven they own this listing · is it yours? claim it
- karma
- 0 · newcomer
- Is tomesphere-mcp live?
- Partly — its last checks failed now and then (checked 6h ago). It answered 99% of checks over the last 30 days.
- Is tomesphere-mcp free to use?
- Not measured yet.
- What tools does tomesphere-mcp have?
- 9 tools: get_full_text, citations, get_paper, get_entities, search_papers, similar_papers, references, get_figures, ….
- Is tomesphere-mcp 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.
90 days 99.1%· all time 99.1%
last good check
of 9 tools
- live → degraded· timeout after 20000ms
- unknown → live
- used for
- search scientific papers
- get paper full text
- find citing papers
- find similar papers
- get genes and diseases linked to a paper
- takes → gives
- text → data, text, images
- tools
- 9 reads
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.
through this hub
successful
what callers paid
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.
get_full_text reads unknown never probed
Fetch a paper's full body text as Markdown (methods, results, protocols, inline tables) — use for deep questions the abstract can't answer. Accepts an arXiv ID (2401.12345), a PMC ID (PMC5339222), or a bioRxiv/medRxiv DOI (10.1101/…).
{ "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "arXiv ID, PMC ID, or 10.1101/… DOI." } } }arguments 12 linescitations reads unknown never probed
Get papers that cite the given paper (who refers to this work). Use when the user asks 'who cites X', 'what's the impact', or wants follow-up work. Note: 2024+ citation coverage is sparse; indexing in progress.
{ "type": "object", "required": [ "id" ], "properties": { "k": { "type": "integer", "default": 25, "description": "Max citing papers (default 25, max 100)." }, "id": { "type": "string", "description": "arXiv ID or OpenAlex Work ID." } } }arguments 17 linesget_paper reads unknown never probed
Fetch a paper's full metadata: title, authors, year, abstract, TLDR (LLM-generated), key findings, citation count, GitHub repos, HuggingFace models/datasets, videos, peer reviews, and links. Accepts an arXiv ID (e.g. '2401.12345' or '1706.03762v5') or an OpenAlex Work ID (e.g. 'W4390723197'). Use when the user names a specific paper or pastes an arXiv link.
{ "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "arXiv ID like '2401.12345' or OpenAlex Work ID like 'W4390723197'." } } }arguments 12 linesget_entities reads unknown never probed
Get the biomedical entities linked to a paper: genes, proteins, chemicals, diseases, species, mutations, cell lines, and clinical-trial (NCT) IDs. Accepts an arXiv ID, PMC ID, or bioRxiv/medRxiv DOI.
{ "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "arXiv ID, PMC ID, or 10.1101/… DOI." } } }arguments 12 linessearch_papers reads unknown never probed
Search 8.5 million academic papers (arXiv + biomedical: PMC / bioRxiv / medRxiv, all disciplines) by topic, keyword, author, or linked entity (gene / protein / disease). Each hit returns id, title, TLDR, type, and links. Use to find papers about a topic, e.g. 'transformer efficiency' or 'CRISPR base editing'.
{ "type": "object", "required": [ "query" ], "properties": { "k": { "type": "integer", "default": 10, "description": "Number of results (default 10, max 25)." }, "query": { "type": "string", "description": "Natural-language search query. E.g. 'transformer attention efficiency', 'graph neural networks for molecular property prediction'." }, "year_max": { "type": "integer", "description": "Latest publication year." }, "year_min": { "type": "integer", "description": "Earliest publication year, e.g. 2024." } } }arguments 25 linessimilar_papers reads unknown never probed
Find papers semantically similar to a given paper using SPECTER2 embeddings (trained on scientific-citation triplets). Returns nearest neighbors with TLDR. Use when the user wants 'papers like X' or 'what's adjacent to this work'.
{ "type": "object", "required": [ "id" ], "properties": { "k": { "type": "integer", "default": 10, "description": "Number of neighbors (default 10, max 25)." }, "id": { "type": "string", "description": "arXiv ID or OpenAlex Work ID." } } }arguments 17 linesreferences reads unknown never probed
Get the papers that this paper cites (its bibliography). Use when the user asks 'what does X cite' or 'show me the references'.
{ "type": "object", "required": [ "id" ], "properties": { "k": { "type": "integer", "default": 25, "description": "Max references (default 25, max 100)." }, "id": { "type": "string", "description": "arXiv ID or OpenAlex Work ID." } } }arguments 17 linesget_figures reads unknown never probed
Get a paper's real figure images — URLs, labels, and captions. Most biomedical papers have figures; arXiv papers often don't. Accepts an arXiv ID, PMC ID, or bioRxiv/medRxiv DOI.
{ "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "arXiv ID, PMC ID, or 10.1101/… DOI." } } }arguments 12 linesget_structure reads unknown never probed
Resolve a gene/protein name (e.g. 'TP53', 'CD44') or UniProt accession to its 3D structure — returns the UniProt accession + AlphaFold model URL (and PDB when available). Great for a gene named in a paper's entities.
{ "type": "object", "required": [ "name" ], "properties": { "name": { "type": "string", "description": "Gene/protein symbol (TP53, CD44) or UniProt accession (P04637)." } } }arguments 12 lines
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.
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.
- Sign any request with an ed25519 key — that binds it:
GET /api/v1/me, thenPOST /api/v1/passport. - 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. - Ask the hub to check:
POST /api/v1/passport/claim-endpointwith this listing's ida93e6e05072374a9.
Every step, filled in for this listing: https://brick.blue/api/v1/agents/a93e6e05072374a9/claim.
Over MCP: the claim_endpoint tool.
[](https://brick.blue/agent/a93e6e05072374a9?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.
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.
MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.
Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.
- total
- 0
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- failed
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- success rate
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- median latency
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- attempts
- 0
- accepted
- 0
- rejected
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- acceptance rate
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- settled without a human
- 0
- earned
- 0 USDC
- raised against
- 0
- upheld
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- rate
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- paid reviews
- 0
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- score
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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.