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Available as MCP tools: paper_search + paper_read — call directly from Claude / Cursor / any MCP client. See MCP Server for the 60-second setup.
Live   1 credit · search   free · read

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What it does for your agent

paper_search returns the most relevant Quant Paper knowledge cards for a natural-language query — research on factors, anomalies, microstructure, ML for finance, and more. Use it as a literature entry point: when an agent needs to ground a claim in academic work (“is the momentum crash effect real?”, “what does the factor zoo paper actually say?”), call paper_search to surface candidate paperCardIds + availableSections, then paper_read to load the exact sections that answer the question. The vectors are built from title + abstract + summary + tags, so a card-level hit is a green light to call paper_read for sections — paper_search deliberately does not return full text.

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Agent flow

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Response

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paper_search response

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data
PaperCard[]
required
Ranked array of paper cards (highest relevance first).
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meta.topK
number
The topK value used for this request.
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meta.creditsUsed
number
Credits consumed by this call (always 1 for search).
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meta.remainingCredits
number
Account credits remaining.
200 OK · paper_search
{
  "data": [
    {
      "paperCardId": "card_abc123",
      "sourcePaperId": "arxiv:1404.4944",
      "title": "Momentum Crashes",
      "authors": ["Kent Daniel", "Tobias J. Moskowitz"],
      "abstract": "Despite their strong positive abnormal returns, momentum strategies experience infrequent but severe crashes...",
      "summary": "Documents that momentum portfolios crash following bear-market rebounds. The crashes are forecastable in real time using market-state and volatility variables.",
      "tags": ["factor", "momentum", "crash"],
      "availableSections": [
        { "section_key": "introduction", "section_type": "introduction", "title": "Introduction", "char_count": 18420, "section_order": 1 },
        { "section_key": "methodology", "section_type": "method", "title": "Methodology", "char_count": 22150, "section_order": 2 }
      ],
      "sectionCount": 6,
      "fullTextCharCount": 102345,
      "pdfUrl": "https://arxiv.org/pdf/1404.4944"
    }
  ],
  "meta": { "topK": 5, "creditsUsed": 1, "remainingCredits": 99 }
}

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paper_read response

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data
PaperReadResult
required
The selected sections of one paper card.
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meta.creditsUsed
number
Always 0 for read.
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meta.remainingCredits
number
Account credits remaining.

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Notes

Two-step lookup is canonical: paper_search returns IDs + summaries + section manifest cheaply (1 credit), then paper_read loads only the section(s) you actually need (free). Read top-1’s introduction + methodology first; pull more sections only when you need to verify a specific claim.
Decide which sections to read before calling paper_read by inspecting availableSections[i].char_count from paper_search. Avoid ["all"] for long papers — pull 1-2 targeted sections to keep agent context small.
Queries longer than 2,000 characters are rejected with 400. Summarize long agent context before calling.
topK is capped at 10 for paper_search. Higher values are silently clamped.
paper_search returns card-level metadata only — no full text. To get section content, you must call paper_read.

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Direct invocation

// 1) Search
{
  "method": "tools/call",
  "params": {
    "name": "paper_search",
    "arguments": { "query": "momentum crash", "topK": 5 }
  }
}

// 2) Read targeted sections from the top hit
{
  "method": "tools/call",
  "params": {
    "name": "paper_read",
    "arguments": {
      "paperCardId": "card_abc123",
      "sections": ["introduction", "methodology"]
    }
  }
}

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Full parameter reference

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query
string
required
Natural-language search query. Max 2,000 characters.
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topK
number
default:5
Maximum results to return. Range 1–10.
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paperCardId
string
required
The paperCardId returned by paper_search.
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sections
string[]
default:["all"]
Section keys from availableSections[].section_key. Pass ["all"] (the default when omitted) to read every section.

Wiki Search

Same two-step pattern over the curated Quant Wiki corpus (concepts, formulas, factors).

MCP Server setup

Connect Claude / Cursor / any harness in 60 seconds.