Search SEC EDGAR full-text for filings.
Args: company_name: Issuer name or keyword. form_type: Filing form (e.g. '10-K', '10-Q', '8-K'). date_from: Earliest filing date (YYYY-MM-DD). limit: Max results (1-100, default 25).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| date_from | No | ||
| form_type | No | ||
| company_name | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'Search' implies a read-only operation, there is no disclosure of side effects, authentication requirements, rate limits, or data freshness. The description is minimal and lacks behavioral context beyond the action itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence plus a bullet-like argument list. It is front-loaded with the purpose and immediately followed by parameter details, with no redundant or unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for basic use but lacks information about the return format or what constitutes a result. Given the absence of an output schema, the agent cannot know if the tool returns filing metadata, URLs, or full text. Context is partially complete but has notable gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description adds value by providing concise semantics for each parameter (e.g., 'Issuer name or keyword' for company_name, format hint YYYY-MM-DD for date_from, range 1-100 for limit). This adequately compensates for the lack of schema descriptions, though some details could be more precise.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Search SEC EDGAR full-text for filings,' clearly identifying the resource (SEC EDGAR) and action (search). The parameter list (company_name, form_type, date_from, limit) further clarifies scope, distinguishing it from sibling tools like mcp_get_sec_filing (retrieve specific filing) and mcp_search_companies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. It only lists parameters, leaving the AI agent to infer usage context without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct public records source (company, SEC, UCC, spending, NPI, courts, licenses) with clear differentiation between search and retrieval operations. Minimal overlap and no ambiguity.
All tools follow a consistent 'mcp_verb_noun' pattern using get, lookup, search, and verify. No mixed conventions or irregular naming.
10 tools cover a broad range of public records domains without being overwhelming. Each tool earns its place by targeting a specific source or operation.
The set covers many common public records, but mcp_get_ucc_filings is a roadmap stub returning not_implemented, which is a significant functional gap. Missing sources like property or criminal records are expected, but the non-functional tool hurts completeness.