EnformionGO API Wrapper

This project is a FastAPI wrapper for a wide range of EnformionGO API endpoints. It simplifies interaction with the EnformionGO API by handling authentication and providing validated request models. It also exposes the API as an MCP-enabled server using fastapi-mcp.

Capabilities

This wrapper provides access to the following categories of EnformionGO APIs:

• Dev APIs (Single Result):
  • Contact Enrichment: Find more data about a contact.
  • Caller ID: Get information for a phone number.
  • Email ID: Get information for an email address.
  • Contact ID: Search for contact info by person ID.
  • Address ID: Find contact info for property owners/residents.
  • Address AutoComplete: Autocomplete addresses.
• People Data:
  • Person Search: Comprehensive search for people.
  • Reverse Phone Search: Find people associated with a phone number.
  • ID Verification: Verify an identity and get a score.
  • Census Search: Search historical population data.
  • Divorce Search: Search for divorce records.
  • LinkedIn ID: Search using a LinkedIn profile URL.
• Property Data:
  • Property Search V2: Search for property data.
• Business Data:
  • Business Search: Search for business information.
  • Domain Search: Search for domain data.
  • Workplace Search: Search for workplace data.
  • Business ID: Search by business ID.

It also features:

• Authentication: Handles authentication with the EnformionGO API using your API credentials.
• Request Validation: Uses Pydantic models to validate request bodies.
• MCP Server: Exposes the API as an MCP server.

Limitations

• Bring Your Own Key: You must have your own EnformionGO API credentials.
• No Database: This is a pure proxy service and does not have its own database or data persistence layer.
• Basic Error Handling: The API returns basic HTTP exceptions with details from the upstream API or the HTTP client.
• Undefined Schemas: Some newer endpoints (property-search-v2, domain-search, business-id) do not have Pydantic models defined and accept a generic JSON body.

Quickstart Guide

This guide will help you get the EnformionGO API wrapper up and running. You can either use Docker (recommended for production) or run it locally for development.

Prerequisites

• Python 3.13+
• uv for dependency management (if running locally)
• Docker (if using Docker)
• EnformionGO API credentials

1. Configure Credentials

Create a .env file in the root of the project and add your EnformionGO API credentials:

GALAXY_AP_NAME=your_api_name
GALAXY_AP_PASSWORD=your_api_password

2. Run the Application

You have two options for running the application:

Docker (Recommended)

This is the recommended method for a stable deployment.

1. Build the Docker image:

   docker build -t enformiongo .
   

2. Run the container:

   docker run -p 8000:8000 --env-file .env enformiongo
   

Local Development

This method is ideal for development and testing.

1. Install dependencies:

   uv pip sync
   

2. Run the server with auto-reload:

   uvicorn main:app --reload
   

3. Access the API

The application will be accessible at http://localhost:8000.

You can view the interactive API documentation (Swagger UI) at http://localhost:8000/docs.

Usage

Once the application is running, you can connect to it from your client application. The API is available at http://127.0.0.1:8000 by default.

You can also access the interactive API documentation at http://127.0.0.1:8000/docs.

MCP Server

This application also includes an MCP server. You can find the MCP server at http://127.0.0.1:8000/mcp.