EDGAR + Entity: US Company Research

Search SEC registrants

search_company

Read-onlyIdempotent

Find SEC-registered public companies by ticker or name. Matching ignores case, punctuation, '&' vs 'and' and legal suffixes (Inc/Inc./Corp/Corporation/Co/Company/LLC/Ltd...), tolerates typos ('Microsfot' -> Microsoft) and knows well-known former names (matched_former_name, e.g. 'Facebook' -> Meta Platforms). Returns CIK (the SEC id used by every other tool), name, tickers, exchange and a match score (100 = exact ticker, 97 = exact name, < 80 = fuzzy). With no match it returns did_you_mean suggestions. Source: SEC company_tickers_exchange.json (companies with a listed ticker only); private or non-SEC companies: use lookup_business_entity.

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": {
      "query": "<query>"
    },
    "name": "search_company"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`query`	Yes	Ticker or company name, e.g. 'MSFT', 'berkshire', 'Tesla Inc', 'Johnson and Johnson'

Output Schema

Name	Required	Description	Default
`hint`	No
`query`	Yes
`matches`	Yes
`source_url`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 30, 2026

changedInput schema / properties / query / description

Previous value: -"Ticker or company name, e.g. 'MSFT', 'berkshire', 'Tesla Inc'"New value: +"Ticker or company name, e.g. 'MSFT', 'berkshire', 'Tesla Inc', 'Johnson and Johnson'"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "hint": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "matches": {
+      "items": {
+        "additionalProperties": {},
+        "properties": {
+          "cik": {
+            "description": "10-digit CIK",
+            "type": "string"
+          },
+          "exchange": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "name": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "score": {
+            "description": "Match score (100 = exact ticker)",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "tickers": {
+            "anyOf": [
+              {
+                "items": {
+                  "type": "string"
+                },
+                "type": "array"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          }
+        },
+        "required": [
+          "cik"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "query": {
+      "type": "string"
+    },
+    "source_url": {
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "query",
+    "matches"
+  ],
+  "type": "object"
+}

First observedOct 29, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnly, idempotent and openWorld, so safety is covered. The description adds substantial behavioral detail beyond that: normalization rules, typo tolerance, former-name matching, the meaning of match scores, did_you_mean fallback, and the underlying source dataset.

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?

Dense but front-loaded: the core purpose and scope come first, followed by matching behavior, return fields, and the alternative. Every sentence adds distinct information and there is no 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 search tool with an output schema and read-only annotations, the description supplies everything an agent needs: covered dataset, matching behavior, return fields, score interpretation, and fallback behavior. The minor omission of the limit parameter is already covered by the schema.

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 coverage is 50%, with the required query parameter already documented via examples. The description compensates for the gap by explaining the matching semantics applied to the query, though it says nothing about the optional limit parameter beyond what the schema provides.

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 and resource ('Find SEC-registered public companies by ticker or name') and explicitly scopes the tool to SEC registrants with listed tickers. It names the sibling alternative lookup_business_entity for private/non-SEC entities, so an agent can distinguish it from the rest of the toolset.

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?

Explicitly says what the tool covers ('companies with a listed ticker only') and routes to lookup_business_entity for private or non-SEC companies. The coverage boundary and alternative are stated, not implied.

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

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