Search Filing Text

search_filing_text

sp500

full

Semantic search over SEC 10-K and 10-Q narrative sections — Risk Factors, MD&A, Business, Legal Proceedings, and Controls & Procedures. Returns the top passages most similar in meaning to the query, with links back to the source filing.

Example Call

# Using the Valuein MCP server from Python (via MCP SDK)
# Or call directly from Claude / Cursor after setup

result = await client.call_tool(
    "search_filing_text",
    arguments={
    "query": "EXAMPLE"
}
)
print(result)

Direct tool call:search_filing_text(query="supply chain concentration risk in semiconductor manufacturing", section="risk_factors")

Inputs

Parameter	Type	Required	Description
`query`	string	required	Natural-language query. Phrase it as a statement rather than a question for best recall.
`ticker`	string	optional	Restrict search to one company. Omit for cross-company search.
`section`	string	optional	Restrict to a single section label: risk_factors, mdna, business, footnotes, controls_procedures, legal_proceedings, other.
`form_type`	string	optional	Restrict to one form type: 10-K, 10-Q, 10-K/A, 10-Q/A.
`limit`	integer	optional	Max passages to return (1–20). Defaults to 5.

Output Fields

passagestickeraccession_idsectionform_typefiling_datescoresource_url

Example Response

{
  "passages": null,
  "ticker": "AAPL",
  "accession_id": "0000320193-24-000006",
  "section": null,
  "form_type": "10-K",
  "filing_date": "2024-03-15",
  "score": null,
  "source_url": null
}

Returns the top 5 Risk Factor passages across semiconductor 10-K filings that discuss supply-chain concentration, with SEC EDGAR links.

Notes

Status: coming soon — semantic search launches Q3 2026. The tool is registered and callable today but returns a placeholder response until the Vector DB is live.