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Search SEC registrants

edgar_search_companies
Read-onlyIdempotent

Find SEC-registered companies by ticker or partial name to get ticker, CIK, and exchange. Resolve unknown tickers before searching filings.

Instructions

Find companies that file with the SEC (≈10,000 listed registrants) by ticker or name. Returns ticker, name, CIK and exchange. Use it when you are unsure of a ticker; most other tools accept a ticker, CIK or name directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results (default 20).
queryYesTicker or part of the company name, e.g. 'coca', 'BRK'.
response_formatNoOutput format: 'markdown' (readable, default) or 'json' (structured).markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by scoping the search to roughly 10,000 SEC registrants and by specifying the returned fields, which is valuable because there is no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences each earn their place: the first defines the action and scope, the second lists the return fields, and the third gives decision guidance for when to use the tool. There is no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only search with one required parameter and complete schema documentation, the description covers purpose, scope, return values, and usage context. The agent has enough information to decide when to call it and what to expect back.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: query, limit, and response_format all have descriptions, defaults, and examples in the schema itself. The tool description does not meaningfully add parameter-level semantics beyond restating that the query can be a ticker or name, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Find companies that file with the SEC' and explains the two search paths, ticker or name. It also states the exact return fields, which distinguishes it from related search tools like edgar_search_concepts and edgar_full_text_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit usage condition: 'Use it when you are unsure of a ticker.' It also tells the agent that most sibling tools accept a ticker, CIK, or name directly, so the agent can skip this lookup when an identifier is already known.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.