Lucene-style full-text search across the entire SEC EDGAR public-filings corpus since the 1990s. Forms include 10-K (annual), 10-Q (quarterly), 8-K (current event), DEF 14A (proxy), S-1 (IPO), 13F (institutional holdings), and ~70+ others. License: US Government public domain. The killer endpoint...
AI agents call search_sec_edgar to retrieve information from TensorFeed without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
q | string | Yes | Search query (Lucene syntax supported) |
enddt | string | — | End date YYYY-MM-DD |
forms | string | — | Comma-separated form types (e.g. "10-K,10-Q,8-K") |
limit | number | — | Max hits (1-50) |
startdt | string | — | Start date YYYY-MM-DD |
Parameters from the server's own tool schema.
This tool retrieves and queries publicly available financial disclosure documents filed with the SEC. It has no capability to modify, delete, execute code, or trigger financial transactions. The description indicates only search and retrieval functionality over historical public filings.
From the tool's definition Tool description states it performs 'full-text search across the entire SEC EDGAR public-filings corpus' and explicitly characterizes forms as read-only documents (10-K annual reports, 10-Q quarterly reports, proxy statements, IPO filings, institutional…
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
Lucene-style full-text search across the entire SEC EDGAR public-filings corpus since the 1990s. Forms include 10-K (annual), 10-Q (quarterly), 8-K (current event), DEF 14A (proxy), S-1 (IPO), 13F (institutional holdings), and ~70+ others. License: US Government public domain. The killer endpoint for finance and equity-research agents. It is categorised as a Read tool in the TensorFeed MCP Server, which means it retrieves data without modifying state.
search_sec_edgar accepts 5 parameters: q, enddt, forms, limit, startdt. Required: q. The full parameter table on this page comes from the server's own tool schema.
Register the TensorFeed MCP server in PolicyLayer and add a rule for search_sec_edgar: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches TensorFeed. Nothing to install.
search_sec_edgar is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the search_sec_edgar rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for search_sec_edgar. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
search_sec_edgar is provided by the TensorFeed MCP server (https://mcp.tensorfeed.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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