filingrail-mcp

search_companies

Find SEC-registered companies in EDGAR by ticker, CIK, or name fragment; returns CIK, ticker, name, and related details.

Instructions

Search SEC-registered companies by ticker, CIK, or name fragment.

Args: q: search term (e.g. "AAPL", "Apple", "320193") limit: max results (1-100, default 10)

Returns: list of {cik, ticker, name, ...}

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "search_companies"
  }
}

Input Schema

Name	Required	Description	Default
`q`	Yes
`limit`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.3Oct 16, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the return shape and the accepted identifier types, and the parameter bounds, but says nothing about result ordering, case sensitivity, fuzzy vs exact matching, or whether inactive/delisted registrants are included. Adequate for a benign read-only search, but not rich.

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

Conciseness4/5

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

Purpose sentence is front-loaded, followed by a compact Args block and a one-line Returns. Every element earns its place, though restating param names in Args is slightly redundant with the schema; the examples justify the space.

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

Completeness4/5

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

An output schema exists, so the Returns line is a bonus rather than a necessity. With no annotations and a simple two-parameter read, the description covers inputs, bounds, and return shape well enough to call the tool correctly; only matching semantics and result ordering are unaddressed.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate, and it does: it gives concrete example values for q across all three lookup modes ("AAPL", "Apple", "320193") and spells out the limit range and default (1-100, default 10). Only minor gaps remain (no explicit 'required' flag or empty-result behavior).

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

Purpose4/5

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

States a specific verb and resource (search SEC-registered companies) plus the three lookup keys (ticker, CIK, name fragment), which is concrete and unambiguous. It does not explicitly position itself against the siblings (all get_* data fetchers), but the search-vs-fetch distinction is clear from the name and phrasing.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: an agent can infer this is the discovery step before calling get_financials or get_recent_filings, since those need a CIK/ticker. No explicit when-to-use, when-not-to-use, or named alternative is given, so it falls at the 'implied usage' level.

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

Deploy Server