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French Company Verification

company_fr_verify

Verifies the existence and current status of a French company or establishment from a SIREN or SIRET. Use when: You have a French SIREN or SIRET and need to confirm that the company or establishment exists in the public source. You need its current administrative active/closed status before another automated step. Avoid when: You only have a company name and need to discover its identifier; use company/fr/search. You need directors, financials, legal risk or compliance checks; use the corresponding specialized endpoint. Limitations: This verifies public administrative existence and status only; it is not KYC, identity assurance or beneficial-owner verification. Returned fields depend on what the public company source exposes for the identifier. Price: 0.005 USD per call via x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
identifierYes9-digit SIREN or 14-digit SIRET

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes
nameYes
sirenYes
siretYes
activeYes
existsYes
addressYes
identifierYes
postal_codeYes
activity_codeYes
identifier_typeYes

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations provide limited behavioral signal (readOnlyHint=false, idempotentHint=false, destructiveHint=false), and the description adds valuable context: it is not KYC, it only covers public administrative status, and returned fields depend on what the source exposes. It also discloses the paid nature via price, which is useful beyond annotations. No contradiction with annotations is present.

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 with clear sections: purpose, use-when, avoid-when, limitations, and price. Every section earns its place by helping an agent decide when to use the tool, what to expect, and what not to expect. The most important functional statement is front-loaded.

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?

Given a single required parameter, a complete output schema, clear usage guidance, explicit exclusions, and limitations, nothing critical is missing. The description adequately covers what an agent needs to select and invoke the tool correctly without duplicating the output schema.

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?

The schema already fully documents the single 'identifier' parameter with pattern and a description ('9-digit SIREN or 14-digit SIRET'). The description repeats this concept but does not add meaningful new detail about formatting or edge cases beyond the schema, so the baseline schema coverage score of 3 applies.

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 ('Verifies') and names the exact resource: existence and current administrative status of a French company or establishment from a SIREN or SIRET. It also distinguishes itself from siblings by explicitly pointing to company_fr_search for name-based lookup and specialized endpoints for directors, financials, and risk.

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 'Use when' section gives concrete conditions: having a SIREN/SIRET and needing existence/status confirmation before automation. The 'Avoid when' section names alternatives explicitly, including company/fr/search for identifier discovery and specialized endpoints for other data types, so an agent knows exactly when NOT to invoke this tool.

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.

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