INSEE MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@INSEE MCP Serversearch for company with SIRET 44302124100072"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
INSEE MCP Server
MCP (Model Context Protocol) server for accessing INSEE data via the SIRENE API, BDM, and official nomenclatures.
One-line Installation
With uv (recommended)
# Install and launch directly
API_KEY="your_insee_api_key" uv run --with insee-mcp insee-mcpor if you prefer to use uvx
# Install and launch directly
API_KEY="your_insee_api_key" uvx insee-mcp insee-mcpStandard MCP Configuration
Add this to your MCP configuration (e.g., Claude Desktop, or Copilot):
{
"mcpServers": {
"insee": {
"command": "uvx",
"args": ["insee-mcp", "insee-mcp"],
"env": {
"API_KEY": "your_insee_api_key"
}
}
}
}With pipx
API_KEY="your_insee_api_key" pipx run --spec git+https://github.com/KerryanOPMace/mcp-insee.git insee-mcpRelated MCP server: mcp-insee-entreprises
Quick Installation
Direct Installation (recommended)
# Install directly from GitHub
pip install git+https://github.com/KerryanOPMace/mcp-insee.git
# Set your INSEE API key
export API_KEY="your_insee_api_key"
# Start the server
insee-mcpInstallation with pipx (isolated)
# Install with pipx (isolated environment)
pipx install git+https://github.com/KerryanOPMace/mcp-insee.git
# Set the API key
export API_KEY="your_insee_api_key"
# Start the server
insee-mcpDeveloper Installation
# Clone the repository
git clone https://github.com/KerryanOPMace/mcp-insee.git
cd mcp-insee
# Install in development mode
pip install -e .If you wish to contribute to the project, please create issues and branches. You can merge request and then a supervisor will review it before merging
Configuration
INSEE API Key
You must obtain an API key from the INSEE API portal and configure it:
Linux/Mac:
export API_KEY="your_insee_api_key"Windows (PowerShell):
$env:API_KEY="your_insee_api_key"Windows (CMD):
set API_KEY=your_insee_api_keyAvailable Tools
search_company: Search for companies in the SIRENE databaseBy SIREN, SIRET, or company name
Fuzzy search available
STREAMABLE-HTTP TRANSPORT
Server Access
Once started, the MCP server is accessible at:
URL:
http://127.0.0.1:8000/mcpTransport: Streamable HTTP
Client Test
from fastmcp import Client
import asyncio
async def test():
client = Client("http://127.0.0.1:8000/mcp")
async with client:
# List tools
tools = await client.list_tools()
print(tools)
# Search for a company
result = await client.call_tool("search_company", {
"siret": "44302124100072"
})
print(result)
asyncio.run(test())Requirements
Python 3.8+
Valid INSEE API key
Internet access for API requests
STDIO TRANSPORT
Server Access
Once started, the MCP server runs locally according to the standard io protocol
Client Test
from fastmcp import Client
import asyncio
async def test():
client = Client("http://127.0.0.1:8000/mcp")
async with client:
# List tools
tools = await client.list_tools()
print(tools)
# Search for a company
result = await client.call_tool("search_company", {
"siret": "44302124100072"
})
print(result)
asyncio.run(test())Requirements
Python 3.8+
Valid INSEE API key
Internet access for API requests
License
MIT License
Available Tools
1 toolsearch_companyB
Recherche une entreprise dans la base SIRENE selon SIREN, SIRET ou nom.
| Name | Required | Description | Default |
|---|---|---|---|
| company_name | No | Nom de l'entreprise. | |
| siren | No | Code SIREN. | |
| siret | No | Code SIRET. | |
| fuzzy | No | Active la recherche approximative si nom partiel. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states 'search' but does not clarify whether exact or fuzzy matching is default, how results are returned, or any side effects. The fuzzy parameter is in the schema but not highlighted in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence in French, efficient and to the point. However, it could be slightly more structured by separating the search criteria or mentioning the database context more explicitly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description is incomplete. It does not explain the search behavior when multiple parameters are provided, the structure of results, or any limitations. More details are needed for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The tool description adds no extra meaning beyond the schema's parameter descriptions, which are adequate but minimal. No additional context is provided for parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'search' and the resource 'company in the SIRENE database' along with the search criteria (SIREN, SIRET, or name). It is specific enough to distinguish from generic search tools, though no siblings are provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used to search for companies using the given identifiers but does not provide explicit guidance on when to use each parameter or when to avoid this tool. No alternatives are mentioned, which is acceptable without siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no ambiguity. The agent cannot confuse it with any other tool.
Single tool name 'search_company' follows a clear verb_noun pattern, consistent within itself.
A single search tool is too sparse for a domain like INSEE company data, which typically requires multiple operations (e.g., get details, list results, paginate).
The server covers only a basic search, missing essential operations like retrieving full company details, filtering, or pagination, making it severely incomplete for practical use.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
INSEE MCP — France's SIRENE business registry (INSEE).
Search French companies: financials, directors, ownership, M&A and insolvency events.
French & European company registry for AI agents: KYB, sanctions, annual accounts. x402, no API key.
Vérification B2B française : SIRET, SIRENE, dirigeants RNE, santé d'entreprise. Hébergé en France.
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- FlicenseNot gradedqualityDmaintenanceMCP server to query the INSEE SIRENE API and search for French companies, supporting searches by SIREN, SIRET, and advanced filters like name, location, and activity.1
- FlicenseNot gradedqualityDmaintenanceEnables searching for French companies using the official data.gouv.fr API, with filters for name, location, activity, and certifications.1
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