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companylens-mcp

Company Profile

company_profile

Generate comprehensive corporate profiles using verified government data, including SEC filings, financial metrics, UK registration details, and officer information for business analysis.

Instructions

Get a full corporate profile for a company: SEC filings, financials (revenue, net income, assets), UK registration details, officers. Use company_search first to get an entity_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_idYesCompanyLens entity ID from company_search (starts with "companylens_")

Implementation Reference

  • The 'company_profile' tool registration and handler implementation. It uses 'apiCall' to fetch data from the company's profile endpoint based on the provided 'entity_id'.
    // Tool 2: Company profile
    server.registerTool(
      'company_profile',
      {
        title: 'Company Profile',
        description: 'Get a full corporate profile for a company: SEC filings, financials (revenue, net income, assets), UK registration details, officers. Use company_search first to get an entity_id.',
        inputSchema: z.object({
          entity_id: z.string().describe('CompanyLens entity ID from company_search (starts with "companylens_")'),
        }),
      },
      async ({ entity_id }) => {
        const data = await apiCall(`/v1/company/${entity_id}/profile`);
        return {
          content: [{
            type: 'text' as const,
            text: JSON.stringify(data, null, 2),
          }],
        };
      },
    );
Behavior3/5

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

No annotations provided, so description carries full burden. Lists comprehensive data return types (behavioral outcome) but omits operational details: error handling (invalid entity_id), rate limits, caching behavior, or data freshness. Adequate for data scope disclosure but missing operational safety context.

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. First sentence front-loads specific data categories; second provides critical workflow prerequisite. Every word earns its place with no redundancy or generic filler.

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?

For a single-parameter lookup tool without output schema, description adequately compensates by enumerating return data categories. Missing explicit error scenarios or rate limit warnings, but covers essential usage pattern and data scope sufficiently for agent selection.

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 coverage is 100% with detailed parameter description. Description reinforces parameter provenance ('from company_search') which aids workflow understanding, but does not add technical constraints or format details beyond schema. Baseline 3 appropriate for high schema coverage.

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?

Specific verb ('Get') + resource ('corporate profile') with explicit data scope (SEC filings, financials, UK registration, officers). Clearly distinguishes from siblings by contrasting comprehensive profile data vs. specialized data (contracts, court cases, sanctions) and establishing dependency on company_search.

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?

Explicitly states prerequisite workflow ('Use company_search first to get an entity_id'), establishing clear sequence. Lacks explicit guidance on when to use sibling tools instead (e.g., for specific data types like contracts), but provides critical dependency information.

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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