InfoNgen Document Search MCP Server

This is a Model Context Protocol (MCP) server that provides semantic search capabilities using the InfoNgen API. It allows AI assistants to search for documents, news, and other content indexed by InfoNgen.

Features

• Semantic Search: Perform semantic searches against the InfoNgen database.
• Document Retrieval: Retrieves document details including headline, summary, provider, publication date, and URL.
• Content Snippets: Returns relevant content chunks from the documents.

Configuration

The server requires the following configuration, which can be provided via environment variables or command-line arguments:

Installation

Ensure you have Python 3.11 or higher installed.

1. Clone the repository.
2. Install dependencies:

# Install dependencies and set up the environment
uv sync

Usage

Running the Server

You can run the server using uvx. Make sure to set the required environment variables or command line arguments first.

# Set environment variables (example for PowerShell)
$env:API_BASE_URL="https://api.infongen.com/v1"
$env:API_KEY="your-api-key"
$env:OAUTH_TOKEN_URL="https://auth.infongen.com/oauth/token"
$env:OAUTH_CLIENT_ID="your-client-id"
$env:OAUTH_CLIENT_SECRET="your-client-secret"
$env:USER_CONTEXT="your-user-context"

# Run the server
uvx --index-url https://nexus-ci.core.kuberocketci.io/repository/krci-python-group/simple/ --from epmp-igen-document-search-mcp-server mcp-server

Tools

search

Performs a semantic search.

• query (string, required): The text to search for.
• limit (integer, optional): The maximum number of documents to return. Default is 10.

Development

This project uses mcp and requests libraries. The main logic is in main.py which defines the MCP server and tools, and api.py which handles the API communication.