_ registry / mcp streamable-http · checked 8h ago

thequant-space

https://thequant.space

Registry code: 9e92d8e91120b637

api record

thequant.space scores quantitative-finance research papers (arXiv q-fin and SSRN) on two 0-10 axes: math_complexity (theoretical overhead) and empirical_rigor (data quality, costs, out-of-sample validation). Quadrants: Holy Grail (high math, high rigor), Street Traders (low math, high rigor), Lab Rats (high math, low rigor), Philosophers (low math, low rigor). hub_score = 0.6*rigor + 0.4*math is the default ranking. Empirical rigor >= 7 is the credibility bar used across the site. Scores are LLM-assisted rubric judgements, not peer review. Use list_topics / list_methods to learn the filter…

endpoint
https://thequant.space/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
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_ is it live, free and safe measured by this hub
Is thequant-space live?
Yes — it answered the hub's last check (checked 8h ago). It answered 100% of checks over the last 30 days.
Is thequant-space free to use?
Yes — the hub reached it with no key and no payment.
What tools does thequant-space have?
12 tools: get_guide, semantic_search, ask_papers, get_paper, list_guides, compare_quant_research, generate_quant_literature_review, explore_quant_knowledge_graph, ….
Is thequant-space 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
679ms

last good check

priced tools
0

of 12 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 12 tools
3 open 9 never probed 3 of 12 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.

  • corpus_stats open 8h ago

    Totals: papers, with code, average scores, counts by quadrant, by year (with average rigor) and by paper type, and the last update date.

    mcp-tool

    {
  "type": "object",
  "properties": {}
}
    arguments 4 lines
  • list_methods open 8h ago

    The 14 method hubs (econometrics-time-series, stochastic-calculus, deep-learning, reinforcement-learning, ...) with description, counts, rigor share and the slugs of the guides that teach each method's evaluation pitfalls.

    mcp-tool

    {
  "type": "object",
  "properties": {}
}
    arguments 4 lines
  • list_topics open 8h ago

    The 17 topic hubs with slug, description, paper count, share of papers with rigor >= 7, and URLs. Use the slug as the topic filter in search_papers.

    mcp-tool

    {
  "type": "object",
  "properties": {}
}
    arguments 4 lines
  • get_guide unknown never probed

    Full Markdown text of one guide or learning path by slug (from list_guides), e.g. deflated-sharpe-ratio, evaluate-ml-trading-paper, score-guide.

    mcp-tool

    {
  "type": "object",
  "required": [
    "slug"
  ],
  "properties": {
    "slug": {
      "type": "string"
    }
  }
}
    arguments 11 lines
  • semantic_search unknown never probed

    Meaning-based (vector + keyword hybrid) search over the full text of every paper page, practitioner guide, learning path, calculator and post, via Cloudflare AI Search. Use it for natural-language questions ("does momentum survive transaction costs in crypto?") or when search_papers' exact keyword matching finds nothing. Returns pages with a relevance score, a snippet of the best-matching chunk and, for papers, the scores and labels. No filters beyond kind; for structured filtering use search_papers. Metered upstream: at most 25 results per call, and a daily budget; when it is exhausted the tool says so and search_papers keeps working.

    mcp-tool

    {
  "type": "object",
  "required": [
    "q"
  ],
  "properties": {
    "q": {
      "type": "string",
      "maxLength": 300,
      "description": "Natural-language query."
    },
    "kind": {
      "enum": [
        "paper",
        "guide",
        "path",
        "tool",
        "post",
        "page"
      ],
      "type": "string",
      "description": "Restrict to one page kind."
    },
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1
    },
    "rewrite": {
      "type": "boolean",
      "default": false,
      "description": "Let the service rewrite the query for retrieval first (one extra model call)."
    },
    "min_score": {
      "type": "number",
      "maximum": 1,
      "minimum": 0,
      "description": "Drop matches below this relevance score."
    }
  }
}
    arguments 42 lines
  • ask_papers unknown never probed

    Aggregate questions about the corpus (how many papers disclose a Sharpe ratio / report a backtest / have code, the highest or lowest reported Sharpe, annual return or drawdown, averages, top-N, optionally in an asset class, since a year, net of costs) are answered exactly from the database with the papers linked (engine: sql). Otherwise a retrieval-augmented answer: the question is searched semantically over every paper page, guide and tool, and a language model answers ONLY from the retrieved pages, citing them as markdown links. Returns the answer text plus a sources array of {title, url, kind}. Scores quoted in the answer come from the page text; verify with get_paper. Metered (retrieval + generation): 5 calls per minute and a daily budget; when exhausted, use semantic_search / search_papers.

    mcp-tool

    {
  "type": "object",
  "required": [
    "question"
  ],
  "properties": {
    "question": {
      "type": "string",
      "maxLength": 2000,
      "description": "A natural-language question about quant-finance research."
    }
  }
}
    arguments 13 lines
  • get_paper unknown never probed

    Full record for one paper by arXiv id (e.g. 2409.01234), SSRN id (ssrn-1234567) or arXiv URL: abstract, summary, the written 'why this score' rationale, the Mermaid research flowchart, all labels, and five related papers.

    mcp-tool

    {
  "type": "object",
  "required": [
    "paper_id"
  ],
  "properties": {
    "paper_id": {
      "type": "string"
    }
  }
}
    arguments 11 lines
  • list_guides unknown never probed

    Titles, slugs and one-line descriptions of the ~70 guides on evaluating, reproducing and operationalizing quant research, plus the learning paths (sequenced reading orders). Use get_guide for the text.

    mcp-tool

    {
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Optional substring to filter titles and descriptions."
    }
  }
}
    arguments 9 lines
  • compare_quant_research unknown never probed

    Side-by-side comparison of 2 to 10 corpus papers on methodology, datasets, transaction-cost treatment, out-of-sample validation, reproducibility and reported performance. Each cell is labelled author-reported or platform-classified and unknown values are explicit. Paid tool: $0.10 USDC per call via x402 v2 (solana). A call without payment returns a payment-required result.

    mcp-tool

    {
  "type": "object",
  "title": "compare_quant_research input",
  "required": [
    "paper_ids"
  ],
  "properties": {
    "paper_ids": {
      "type": "array",
      "items": {
        "type": "string",
        "maxLength": 200,
        "minLength": 1,
        "description": "arXiv id such as \"2511.08571\", \"arXiv:2511.08571v2\", an arxiv.org URL, or \"ssrn-<n>\"."
      },
      "maxItems": 10,
      "minItems": 2,
      "uniqueItems": true
    },
    "dimensions": {
      "type": "array",
      "items": {
        "enum": [
          "methodology",
          "datasets",
          "transaction_costs",
          "out_of_sample_validation",
          "reproducibility",
          "reported_performance"
        ]
      },
      "default": [
        "methodology",
        "datasets",
        "transaction_costs",
        "out_of_sample_validation",
        "reproducibility",
        "reported_performance"
      ],
      "maxItems": 6,
      "minItems": 1,
      "description": "Dimensions to compare; all six when omitted.",
      "uniqueItems": true
    }
  },
  "description": "Compare 2 to 10 corpus papers across selected dimensions. Paper ids are normalised (arXiv URL/prefix/version stripped); ids that normalise to the same paper are rejected; the order of paper_ids does not matter.",
  "additionalProperties": false
}
    arguments 48 lines
  • generate_quant_literature_review unknown never probed

    Source-grounded literature review for a quantitative-finance research question: ranked relevant papers, optional books, methodological comparison, supporting and contradictory evidence, limitations and open questions. Every claim cites corpus sources. Paid tool: $0.25 USDC per call via x402 v2 (solana). A call without payment returns a payment-required result.

    mcp-tool

    {
  "type": "object",
  "title": "generate_quant_literature_review input",
  "required": [
    "research_question"
  ],
  "properties": {
    "max_papers": {
      "type": "integer",
      "default": 10,
      "maximum": 15,
      "minimum": 1
    },
    "include_books": {
      "type": "boolean",
      "default": false,
      "description": "Also list relevant books (catalogue metadata only)."
    },
    "output_format": {
      "enum": [
        "json",
        "markdown"
      ],
      "default": "json",
      "description": "markdown adds a rendered `markdown` field next to the structured sections."
    },
    "research_question": {
      "type": "string",
      "maxLength": 500,
      "minLength": 10,
      "description": "Plain-language question of 10 to 500 characters; runs of whitespace are collapsed."
    },
    "include_contradictory_evidence": {
      "type": "boolean",
      "default": true
    }
  },
  "description": "Generate a source-grounded literature review for a quantitative-finance research question from the corpus.",
  "additionalProperties": false
}
    arguments 40 lines
  • explore_quant_knowledge_graph unknown never probed

    Typed neighbourhood of a topic, method, paper, book or author in the quant knowledge graph, with stable ids, deterministic ordering, per-edge provenance and an explicit verified or inferred flag. Depth up to 3, up to 100 nodes. Paid tool: $0.02 USDC per call via x402 v2 (solana). A call without payment returns a payment-required result.

    mcp-tool

    {
  "type": "object",
  "title": "explore_quant_knowledge_graph input",
  "required": [
    "entity_type",
    "entity_id"
  ],
  "properties": {
    "entity_id": {
      "type": "string",
      "maxLength": 100,
      "minLength": 1,
      "description": "Slug or id: topic/method slug (\"market-microstructure\", \"topic:market-microstructure\"), paper id (\"2511.08571\", \"paper:2511.08571\"), book id (\"bw_...\", \"be_...\") or slug, author id (\"bp_...\") or slug."
    },
    "max_depth": {
      "type": "integer",
      "default": 2,
      "maximum": 3,
      "minimum": 1
    },
    "max_nodes": {
      "type": "integer",
      "default": 50,
      "maximum": 100,
      "minimum": 1
    },
    "entity_type": {
      "enum": [
        "topic",
        "book",
        "author",
        "paper",
        "method"
      ]
    },
    "relationships": {
      "type": "array",
      "items": {
        "enum": [
          "books",
          "authors",
          "papers",
          "topics",
          "methodologies"
        ]
      },
      "default": [
        "books",
        "authors",
        "papers",
        "topics",
        "methodologies"
      ],
      "maxItems": 5,
      "minItems": 1,
      "description": "Kinds of neighbours to traverse: books (book and edition nodes), authors, papers, topics, methodologies (method nodes). All when omitted.",
      "uniqueItems": true
    }
  },
  "description": "Traverse the quant knowledge graph around one entity.",
  "additionalProperties": false
}
    arguments 62 lines
  • search_papers unknown never probed

    Search and filter the 5,000+ scored quant-finance papers. Returns compact records (scores, quadrant, topics, methods, authors, summary, paper_url, page_url) plus the total match count. Combine filters; use min_rigor 7 for credible empirical work; set has_code true for reproducible papers. Reported performance (sharpe, annual_return_pct, max_drawdown_pct, sample_start/end, transaction_costs, out_of_sample) is included when the paper discloses a backtest: filter with has_sharpe / min_sharpe and sort by sharpe or annual_return to answer 'how many papers disclose a Sharpe' or 'highest reported return' questions (use total for counts). Execution-realism flags (tcost_modeled, oos_method, data_resolution, evaluation_type) say whether trading results are net of costs and validated out of sample; empirical_rigor is capped at 6.0 when they are not (empirical_rigor_raw keeps the uncapped score). Follow up with get_paper for the abstract, score rationale and flowchart.

    mcp-tool

    {
  "type": "object",
  "properties": {
    "q": {
      "type": "string",
      "description": "Free-text search over title, abstract, keywords and authors (terms are ANDed)."
    },
    "sort": {
      "enum": [
        "hub_score",
        "rigor",
        "math",
        "date",
        "sharpe",
        "annual_return",
        "drawdown",
        "relevance"
      ],
      "type": "string",
      "description": "Default: relevance when q is given, otherwise hub_score. sharpe / annual_return / drawdown sort by the paper's reported figures (papers without one last)."
    },
    "type": {
      "enum": [
        "empirical",
        "theoretical",
        "methodological",
        "survey-review",
        "perspective-policy",
        "dataset-benchmark",
        "software-tool"
      ],
      "type": "string",
      "description": "Paper type from the classifier."
    },
    "asset": {
      "type": "string",
      "description": "Asset-class slug: equities, crypto, derivatives, fixed-income, commodities-energy, fx, credit, insurance, macro-multi-asset, esg-climate, private-markets, real-estate."
    },
    "limit": {
      "type": "integer",
      "default": 20,
      "maximum": 100,
      "minimum": 1
    },
    "order": {
      "enum": [
        "desc",
        "asc"
      ],
      "type": "string"
    },
    "since": {
      "type": "string",
      "description": "Earliest paper date, YYYY-MM-DD."
    },
    "topic": {
      "type": "string",
      "description": "Topic-hub slug, e.g. market-microstructure. See list_topics."
    },
    "until": {
      "type": "string",
      "description": "Latest paper date, YYYY-MM-DD."
    },
    "author": {
      "type": "string",
      "description": "Author name substring."
    },
    "method": {
      "type": "string",
      "description": "Method slug, e.g. deep-learning. See list_methods."
    },
    "offset": {
      "type": "integer",
      "default": 0,
      "maximum": 1000,
      "minimum": 0
    },
    "has_code": {
      "type": "boolean",
      "description": "Only papers with (true) or without (false) a public code link."
    },
    "max_math": {
      "type": "number",
      "maximum": 10,
      "minimum": 0
    },
    "min_math": {
      "type": "number",
      "maximum": 10,
      "minimum": 0
    },
    "quadrant": {
      "enum": [
        "Holy Grail",
        "Street Traders",
        "Lab Rats",
        "Philosophers"
      ],
      "type": "string"
    },
    "max_rigor": {
      "type": "number",
      "maximum": 10,
      "minimum": 0
    },
    "min_rigor": {
      "type": "number",
      "maximum": 10,
      "minimum": 0
    },
    "has_sharpe": {
      "type": "boolean",
      "description": "Only papers that disclose (true) a Sharpe ratio for their own strategy."
    },
    "max_sharpe": {
      "type": "number",
      "maximum": 50,
      "minimum": -10
    },
    "min_sharpe": {
      "type": "number",
      "maximum": 50,
      "minimum": -10,
      "description": "Reported Sharpe ratio at least this."
    },
    "oos_method": {
      "type": "string",
      "description": "Out-of-sample validation; one or more of: holdout, walk-forward, cross-validation, none, unclear."
    },
    "has_backtest": {
      "type": "boolean",
      "description": "Only papers that report (true) or do not report (false) a backtest of their own strategy on real market data."
    },
    "max_drawdown": {
      "type": "number",
      "maximum": 100,
      "minimum": 0,
      "description": "Reported maximum drawdown (%) at most this."
    },
    "rigor_capped": {
      "type": "boolean",
      "description": "Only papers whose Empirical Rigor was (true) or was not (false) capped at 6.0 for missing transaction costs or out-of-sample testing."
    },
    "tcost_modeled": {
      "type": "string",
      "description": "Transaction costs applied to the reported results; one or more (comma-separated) of: yes, partial, no, n/a, unclear."
    },
    "data_resolution": {
      "type": "string",
      "description": "Finest market data used; one or more of: l2-book, tick, intraday-bars, daily, weekly-monthly, synthetic, none, unclear."
    },
    "evaluation_type": {
      "type": "string",
      "description": "Headline empirical result; one or more of: trading-pnl, execution-cost, forecast-accuracy, pricing-calibration, none."
    },
    "min_annual_return": {
      "type": "number",
      "description": "Reported annualized return (%) at least this."
    }
  }
}
    arguments 161 lines
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