infobel-api-mcp

Python client and MCP server for the Infobel GetData API.

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Installation

From PyPI:

pip install infobel-api-mcp

For local development:

pip install -e .

Requires Python 3.10+.

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Quick start — configure your agent

After installing, run one command to wire infobel-mcp into your agent host:

# User-global config (prompts for credentials)
infobel-mcp add claude       # writes ~/.claude.json
infobel-mcp add codex        # writes ~/.codex/config.toml
infobel-mcp add gemini       # writes ~/.gemini/settings.json (uses env var placeholders)

# Project-local config (cwd)
infobel-mcp add claude --local
infobel-mcp add codex  --local
infobel-mcp add gemini --local

# Project-local config at a specific path
infobel-mcp add claude --local /path/to/project

# Skip the interactive prompts
infobel-mcp add claude --username myuser --password mypass

# Write ${INFOBEL_USERNAME}/${INFOBEL_PASSWORD} placeholders instead of literal creds
infobel-mcp add claude --use-env-vars

After running the command, set your credentials as environment variables:

export INFOBEL_USERNAME="your-username"
export INFOBEL_PASSWORD="your-password"

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Configuration

Set your credentials as environment variables:

export INFOBEL_USERNAME="your-username"
export INFOBEL_PASSWORD="your-password"

Or pass them directly when creating a client:

from infobel_api import InfobelClient

client = InfobelClient(username="your-username", password="your-password")

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Python client

Basic search

from infobel_api import InfobelClient

with InfobelClient() as client:
    result = client.search.search(country_codes="GB", business_name="Acme")

    print(result["counts"]["total"])       # total matching businesses
    print(result["firstPageRecords"])      # [] by default

return_first_page defaults to False, so search() returns counts and a searchId without embedding records unless you explicitly opt in.

Get specific fields (recommended for large result sets)

with InfobelClient() as client:
    # Start a search
    result = client.search.search(
        country_codes="US",
        business_name="Tesla",
    )
    search_id = result["searchId"]

    # Fetch page 1 with only the fields you need
    page = client.search.post_records(
        search_id,
        page=1,
        fields=["uniqueID", "businessName", "phone", "email", "city"],
    )
    for record in page["records"]:
        print(record)

    # Fetch page 2
    page2 = client.search.post_records(search_id, page=2, fields=["uniqueID", "businessName"])

Fetch a full record by unique ID

with InfobelClient() as client:
    record = client.record.get(country_code="US", unique_id="0226550061")
    print(record["businessName"], record["phone"])

Other filters

with InfobelClient() as client:
    # By national ID
    result = client.search.search(country_codes="BE", national_id="0123456789")

    # Businesses with email in a city
    result = client.search.search(
        country_codes="FR",
        city_names="Paris",
        has_email=True,
    )

    # Filter by employee count
    result = client.search.search(
        country_codes="DE",
        employees_total_from=50,
        employees_total_to=200,
    )

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MCP server

The package ships an MCP server that exposes the Infobel API as tools for AI agents (Claude, etc.).

Quick install for Claude Code

After installing the package, register the MCP server with:

infobel-mcp add claude

This automatically uses the Python executable that has the package installed, regardless of whether you are in a venv, conda environment, or using the system Python.

Configure Claude Code manually

As of March 18, 2026, Claude Code stores MCP servers in:

• User scope: ~/.claude.json
• Project scope: /path/to/project/.mcp.json

On Windows, ~/.claude.json maps to your home directory, typically %USERPROFILE%\\.claude.json.

Add this to either file:

{
  "mcpServers": {
    "infobel": {
      "type": "stdio",
      "command": "/path/to/your/python",
      "args": ["-m", "infobel_api.mcp_server"],
      "env": {
        "INFOBEL_USERNAME": "your-username",
        "INFOBEL_PASSWORD": "your-password"
      }
    }
  }
}

Replace /path/to/your/python with the Python executable that has infobel-api-mcp installed. To find it, run this inside the environment where the package is installed:

python -c "import sys; print(sys.executable)"

For a venv the path typically looks like /path/to/project/venv/bin/python. For conda it looks like /opt/conda/envs/myenv/bin/python. The infobel-mcp add claude command above handles this automatically.

Configure Gemini CLI manually

Gemini CLI stores MCP servers in:

• User scope: ~/.gemini/settings.json
• Project scope: /path/to/project/.gemini/settings.json

On Windows, ~/.gemini/settings.json maps to your home directory, typically %USERPROFILE%\\.gemini\\settings.json.

Add this to the settings.json file:

{
  "mcpServers": {
    "infobel": {
      "command": "/path/to/your/python",
      "args": ["-m", "infobel_api.mcp_server"],
      "env": {
        "INFOBEL_USERNAME": "${INFOBEL_USERNAME}",
        "INFOBEL_PASSWORD": "${INFOBEL_PASSWORD}"
      }
    }
  }
}

Replace /path/to/your/python with the Python executable that has infobel-api-mcp installed (see the note in the Claude Code section above). If your settings.json already contains other top-level keys, merge the mcpServers block into the existing file instead of replacing it.

Configure Codex manually

Codex stores MCP servers in:

• User scope: ~/.codex/config.toml
• Project scope: /path/to/project/.codex/config.toml

On Windows, ~/.codex/config.toml maps to your home directory, typically %USERPROFILE%\\.codex\\config.toml.

Add this to config.toml:

[mcp_servers.infobel]
command = "/path/to/your/python"
args = ["-m", "infobel_api.mcp_server"]

[mcp_servers.infobel.env]
INFOBEL_USERNAME = "your-username"
INFOBEL_PASSWORD = "your-password"

Replace /path/to/your/python with the Python executable that has infobel-api-mcp installed (see the note in the Claude Code section above). Codex CLI and the Codex IDE extension share the same MCP configuration.

Available tools

Tool	Description
search_businesses	Search by name, location, category, and more
get_search_results	Fetch additional pages from a previous search
get_record	Get a full business record by unique ID
get_record_partial	Get a lightweight record by unique ID
get_categories_infobel	Browse Infobel category tree
get_categories_international	Browse ISIC categories
get_categories_local	Browse local/national categories
get_locations_cities	List cities for a country
get_locations_regions	List regions for a country
get_locations_provinces	List provinces for a country
get_available_countries	List all available countries
get_languages	List available display languages
test_connection	Verify API connectivity

Example MCP interaction

Once configured, you can ask Claude things like:

"Find all Italian restaurants in Brussels with a phone number."

Claude will call search_businesses with the right filters and return structured results. You tell it which fields you care about:

"Search for Google offices in the US — I only need the business name, address, and phone number."

The record_fields parameter controls what comes back (pass [] for counts only):

search_businesses(
  country_codes=["US"],
  business_name=["Google"],
  record_fields=["businessName", "address1", "city", "phone"]
)

To get more pages, use the searchId from the first call:

get_search_results(
  search_id=12345,
  page=2,
  record_fields=["businessName", "address1", "city", "phone"]
)

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Error handling

from infobel_api import InfobelAPIError, AuthenticationError, RateLimitError, NetworkError

try:
    result = client.search.search(country_codes="GB", business_name="Acme")
except AuthenticationError:
    print("Invalid credentials")
except RateLimitError:
    print("Rate limited — retries are automatic")
except NetworkError:
    print("Connection issue")
except InfobelAPIError as e:
    print(f"API error {e.status_code}: {e.message}")

The client handles rate limiting and retries automatically.

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