Skip to main content
Glama
pgeneralpl

edgar-entity-mcp

by pgeneralpl

Company profile (EDGAR)

get_company_profile
Read-onlyIdempotent

Fetch a company's SEC EDGAR identity: name, tickers, exchange, SIC industry, incorporation state, fiscal year end, EIN, and latest 10-K/10-Q before deeper research.

Instructions

Company profile from SEC EDGAR submissions: legal name, tickers, exchanges, SIC code + industry, state of incorporation, fiscal year end, EIN, filer category, business/mailing addresses, former names, latest 10-K/10-Q. Use it to orient before deeper research.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesTicker (AAPL), CIK (320193 or 0000320193), or company name. Names must resolve unambiguously; use search_company first if unsure.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already carry the full safety profile (readOnly, idempotent, openWorld, non-destructive), so the bar is low. The description adds the data-provenance detail ('from SEC EDGAR submissions') and the scope of returned fields, though it says nothing about pagination, freshness, or rate limits.

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?

Two sentences, zero waste, with the resource/scope front-loaded and the usage cue at the end. Nothing extraneous or duplicated.

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?

With no output schema, the description takes on the burden of describing the return payload and does so thoroughly via the field list. An agent has enough to decide whether the tool returns what it needs before calling.

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?

There is only one parameter and schema coverage is 100%, so the schema already documents the accepted forms (ticker/CIK/name) and only 3 is warranted as a baseline. The description adds no semantics beyond what the schema's parameter description already states.

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?

States a specific verb+resource ('Company profile from SEC EDGAR submissions') and enumerates the concrete payload (name, tickers, SIC, EIN, former names, latest 10-K/10-Q). This clearly separates it from siblings like search_company or list_filings without the agent opening any schema.

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

Usage Guidelines4/5

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

'Use it to orient before deeper research' gives clear when-to-use context for this lookup-style tool. It does not, however, name the alternative (search_company) for ambiguous inputs or state when-not to use it, so it stops short of full routing guidance.

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