SEC EDGAR Filings MCP
SEC EDGAR MCP: search, preview, purchase filings. x402 USDC on Polygon. xpay + Cloud Run upstream.
| Endpoint | https://sec-filings-mcp-1065601264332.us-central1.run.app/mcp (streamable-http) |
|---|---|
| Registry version | 1.0.2 |
| Now | 3 tools · grade C (73) · pin ts_55228b0bb86c51f248ad299326b1e45d · protocol 2025-06-18 |
| First / last listed | 2026-11-06 03:12 UTC / 2026-11-06 03:12 UTC |
| Grade over time | 2026-11-06: C (73), 3 tools |
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Tools: search_filings get_filing_sample purchase_filing
search_filings |
PRIMARY discovery tool — lightweight catalog over 10k+ SEC filings (fi_listings_portfolio).
[COST: low xpay per-call fee]
Does NOT return alpha_signals, causality_events, or financial_metrics (use get_filing_sample / purchase_filing).
Always returns agent_readiness_score (higher = better structured data) and edgar_url.
Required: at least one of ticker, form_type, company_name, fiscal_period, cik params: ticker, form_type, company_name, fiscal_period, cik, min_agent_readiness_score, limit, offset, include_one_liner |
get_filing_sample |
Free preview of one SEC filing (agent-friendly compact row from fi_listings_portfolio_compact).
[COST: $0]
Includes agent_summary and financial_metrics (CompanyFacts-derived) but NOT full
alpha_signals / causality_events — those ship only via purchase_filing after x402 payment.
Compare with purchase_filing: sample = evaluate quality; purchase = full evidence-backed JSON.
[EXAMPLE ARGUMENTS - MIN params: document_id |
purchase_filing |
Purchase and deliver one full SEC filing row from fi_listings_portfolio (MPP v1.0 x402).
[COST: xpay per-call + on-chain USDC data price (see FINANCE_FILING_PRICE_USD)]
Full JSON includes alpha_signals with evidence_verified causality_events and financial_metrics
from SEC CompanyFacts. Do NOT return agent_bundle or internal pipeline fields.
[AGENTIC WORKFLOW — mandatory 2-step 402 flow]:
STEP 1: params: document_id*, network, tx_hash |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.