HelpMyAgent

French Company Search

company_fr_search

Searches French companies by name, SIREN, SIRET or optional location criteria and returns structured matching company records. Use when: You need to find a French company or establishment from a name, legal name, SIREN or SIRET. You need candidate company identifiers before calling a more specialized Company endpoint. Avoid when: You already have an exact SIREN or SIRET and only need to verify existence or administrative status; use company/fr/verify. You need detailed profile, financial, legal-risk or compliance data; use the specialized endpoint or company/fr/intelligence. Limitations: Matching quality and result ordering depend on the public company-search source and the ambiguity of the query. The response is a search result set, not a complete company dossier. Price: 0.002 USD per call via x402.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of matching companies to return
`query`	Yes	Company name, legal name, SIREN or SIRET to search for
`postal_code`	No	Optional French postal code used to narrow the search

Output Schema

TableJSON Schema

Name	Required	Description	Default
`results`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A4.5/5.0

Behavior4/5

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

The description adds useful behavioral context beyond annotations: matching quality is source-dependent, result ordering is not guaranteed, and the response is a search result set rather than a full company dossier. The readOnlyHint=false is not explicitly contradicted since the description never claims a guarantee of no side effects.

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?

The description is well-structured and efficient: a front-loaded summary sentence, then clear Use/Avoid sections, limitations, and pricing. Every sentence earns its place and no filler is present.

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 simple three-parameter search tool with an output schema, the description covers purpose, alternatives, limitations, and pricing. If anything, it is more complete than most tool descriptions of this complexity.

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 description coverage is 100%, so the baseline is 3. The description adds minor semantic color by clarifying that query can be a name, legal name, SIREN, or SIRET, and that postal_code is a location filter, but it does not provide substantial meaning beyond the schema.

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?

The description uses a specific verb ('Searches') and identifies the exact resources: French companies by name, SIREN, SIRET, or location criteria. It also distinguishes itself from specialized endpoints by positioning it as a candidate-identifier search tool.

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?

The description provides explicit 'Use when' and 'Avoid when' guidance, naming concrete alternatives such as company/fr/verify and company/fr/intelligence. An agent can reliably decide when this tool is appropriate versus when a sibling should be used.

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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TDQS

B3.3/5.0

Disambiguation3/5

Most endpoints target distinct resources, but several clusters are easy to confuse: company_fr_intelligence vs company_fr_kyb, company_fr_peers vs company_fr_competitors vs company_fr_public_contract_competitors, and company_fr_risk vs company_fr_default_score vs company_fr_payment_context. The descriptive names help, but the repetitive 'Use when' sections often restate the description rather than contrasting with nearby tools.

Naming Consistency4/5

The dominant convention is domain_fr_feature with consistent snake_case, e.g., company_fr_profile, company_fr_financials, company_fr_public_contracts, procurement_fr_search, which makes the family predictable. The three meta tools (describe_api, list_categories, search_apis) switch to a bare verb_noun style, and a few company_fr names use verbs while most use nouns, creating a minor inconsistency.

Tool Count2/5

With 30 tools, the surface exceeds the 25+ threshold and feels heavy for an agent to navigate, especially because aggregators like company_fr_intelligence and company_fr_kyb overlap with many single-purpose endpoints. The broad French-company data domain justifies a large number of endpoints, but several could be consolidated or split out to make the server more focused.

Completeness4/5

The set covers discovery, verification, profile, directors, financials, legal risk, compliance, public contracts, procurement, funding, benchmarking, signals, and aggregation, so core French-company workflows have no major dead ends. Minor gaps remain around beneficial-ownership/shareholder data and subscription-style monitoring, but those are explicitly outside the stated scope of most endpoints.

Resources

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