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Contextual MCP Server

by ContextualAI

The Contextual MCP Server provides RAG (Retrieval-Augmented Generation) capabilities using Contextual AI, integrating with various MCP clients like Cursor IDE and Claude Desktop. It acts as a bridge between AI interfaces and a specialized Contextual AI agent.

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What is Contextual MCP Server?

This MCP server acts as a bridge between AI interfaces (Cursor IDE or Claude Desktop) and a specialized Contextual AI agent, enabling query processing, intelligent retrieval from a knowledge base, and context-aware responses grounded in source documentation with citations.

How to use Contextual MCP Server?

To use this server, clone the repository, create and activate a virtual environment, install dependencies, configure the server with your Contextual AI API key and agent ID, and integrate it with your AI interface (Cursor IDE or Claude Desktop) by creating or modifying the MCP configuration file in the appropriate location.

Key features of Contextual MCP Server

  • Accurate Responses grounded in documentation

  • Source Attribution with references to source documents

  • Context Awareness maintaining conversation context

  • Real-time Updates reflecting the latest documentation

Use cases of Contextual MCP Server

  • Answering domain-specific questions using a dedicated Contextual AI agent

  • Searching through comprehensive information in a knowledge base

  • Generating responses grounded in source documentation with citations

  • Maintaining conversation context for follow-up questions

FAQ from Contextual MCP Server

What is the purpose of the MCP server?

The MCP server bridges AI interfaces like Cursor IDE and Claude Desktop with a Contextual AI agent to provide RAG capabilities.

What are the prerequisites for using the server?

You need Python 3.10 or higher, Cursor IDE and/or Claude Desktop, a Contextual AI API key, and an MCP-compatible environment.

How do I configure the server?

You need to configure the server with your Contextual AI API key and agent ID, and customize the docstring for your RAG agent to match your knowledge domain.

How do I integrate the server with Cursor IDE or Claude Desktop?

Create or modify the MCP configuration file (mcp.json) in the appropriate location (.cursor/ or Claude Desktop configuration directory) with the correct command and arguments.

What are the limitations of the server?

The server runs locally, tool responses are subject to Contextual AI API limits, and it currently only supports stdio transport mode.