Skip to main content
Glama
yoanbernabeu

MCP Recherche d'entreprises

by yoanbernabeu
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Les deux outils ont des finalités clairement distinctes : le premier permet une recherche générale par critères (nom, activité, localisation), le second se limite à une recherche géographique autour d'un point. Il n'y a pas de chevauchement.

    Naming Consistency5/5

    Les noms suivent un schéma cohérent : 'rechercher_entreprise' comme base, avec un qualificatif pour la variante géographique. La convention snake_case est uniforme et prédictible.

    Tool Count3/5

    Avec seulement 2 outils, le serveur est très ciblé. Pour un service de recherche d'entreprises, cela peut suffire si l'objectif est limité à la recherche, mais le nombre est à la limite inférieure de ce qui est raisonnable.

    Completeness4/5

    Les deux modes de recherche (général et géographique) couvrent les cas d'usage courants. Il manque peut-être une recherche par identifiant unique (SIRET) ou des opérations CRUD, mais dans le cadre d'un serveur dédié à la recherche, l'ensemble est presque complet.

  • Average 3/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    No annotations provided, so the description must disclose behavioral traits. It only says 'searches many criteria' without mentioning pagination, rate limits, response format, or any side effects. This is insufficient for an agent to understand the tool's behavior.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single sentence, concise and front-loaded. It conveys the core purpose without extraneous text. However, it could be slightly more informative while maintaining brevity.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's complexity (32 parameters) and the absence of output schema, the description is too brief. It lacks details about return values, pagination, and API source. The sibling tool's presence also suggests a need for clearer context on when to use this one.

    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 input schema has 100% coverage with detailed descriptions for all 32 parameters. The description adds no new meaning beyond 'numerous criteria'. Baseline 3 is appropriate as the schema handles the parameter documentation.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states it searches French companies using multiple criteria like name, activity, location. It includes examples, but does not explicitly differentiate from the sibling tool 'rechercher_entreprise_geographiques', which likely focuses on geographic search.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance on when to use this tool versus alternatives. Given the sibling tool exists, explicit context or when-not-to-use instructions are missing. The description does not mention any prerequisites or scenario-specific advice.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations are provided, so the description must convey behavioral traits. It only mentions basic parameters but lacks details on pagination, sorting, error handling, or result behavior (e.g., ordering by distance). The vague 'etc.' indicates incomplete disclosure.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single short sentence, which is concise but lacks structure. It uses 'etc.' which is vague and unprofessional.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool has 9 parameters, no output schema, and no annotations, the description is insufficient. It omits details on optional filters (activity types, pagination, minimal response) and does not explain the response structure.

    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 schema already documents all parameters. The description adds minimal extra meaning beyond mentioning lat, lon, radius, and 'etc.' 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 clearly states the tool searches for companies around a geographic point, specifying key parameters (latitude, longitude, radius). It distinguishes from sibling tool 'rechercher_entreprise' which likely lacks geographic constraints.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    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 any exclusions or context. It merely describes what the tool does without usage context.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

mcp-recherche-entreprises MCP server

Copy to your README.md:

Score Badge

mcp-recherche-entreprises MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/yoanbernabeu/mcp-recherche-entreprises'

If you have feedback or need assistance with the MCP directory API, please join our Discord server