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Search French Companies in Sirene

insee.company.search
Read-onlyIdempotent

Search French legal units (companies, associations, sole traders) in the INSEE Sirene national registry using a Lucene-style filter query. Supports filtering by company name (denominationUniteLegale), NAF activity code (activitePrincipaleUniteLegale, e.g. "62.01Z" for software publishing), administrative status (etatAdministratifUniteLegale: A=active, C=ceased), and legal category code (categorieJuridiqueUniteLegale, e.g. 5710 for SA). Combine clauses with AND / OR operators. Returns SIREN, name, acronym, status, NAF code, legal category, and creation date for each matching company. Use insee.company.by_siren to retrieve full details for a specific SIREN number.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesLucene-style filter expression on legal-unit fields. Examples: "denominationUniteLegale:AIRBUS" searches by company name; "activitePrincipaleUniteLegale:62.01Z" searches by NAF activity code; "etatAdministratifUniteLegale:A" returns only active companies (A=active, C=ceased); "categorieJuridiqueUniteLegale:5710" searches by legal category code. Combine with AND / OR operators.
maxNoMaximum number of results to return (1–20, default 10).
offsetNoZero-based starting offset for pagination (default 0).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the bar is lowered. The description adds useful behavioral context: it explains the query syntax, the specific fields searched, and the returned fields (SIREN, name, status, NAF, etc.), which go beyond the schema and annotations. No contradictions.

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 compact and well-structured: it opens with the core purpose, then details filter fields and operators, lists return fields, and ends with a pointer to the sibling tool. Every sentence earns its place; no redundancy.

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 an output schema present, return values are defined. The description covers query capabilities, filter options, operators, and the alternative tool for more detail. Pagination is handled by the schema (max, offset). It is fully adequate for an agent to call this tool correctly.

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% – every parameter (q, max, offset) already has a detailed description with examples. The description reinforces the q syntax and field names but does not add meaning beyond the schema, so the baseline of 3 is appropriate.

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 states a specific action (search) on a defined resource (French legal units in INSEE Sirene) and enumerates the filterable fields (name, NAF code, status, legal category) with examples. It differentiates from the sibling insee.company.by_siren by noting that tool retrieves full details, and implicitly separates it from insee.establishment.search by focusing on legal units.

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?

It provides explicit guidance on query construction (Lucene-style, AND/OR operators) and points to insee.company.by_siren for full details, making the distinction clear. It does not explicitly mention when to use establishment.search instead, but the focus on legal units vs. establishments is implied, leaving a minor gap.

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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