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MCP Server

MCP Chat

A command-line interface application that enables interaction with LLMs through document retrieval, command-based prompts, and extensible tool integrations using the Model Control Protocol architecture.

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8/18/2025
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Please check the documentation below.

README Documentation

MCP Chat

MCP Chat is a command-line interface application. The application supports document retrieval, command-based prompts, and extensible tool integrations via the MCP (Model Control Protocol) architecture.

Prerequisites

  • Python 3.9+
  • Any Chat Completions LLM API Key and Provider (i.e: Gemini)

Setup

Step 1: Configure the environment variables

  1. Create or edit the .env file in the project root and verify that the following variables are set correctly:
LLM_API_KEY=""  # Enter your GEMINI API secret key
LLM_CHAT_COMPLETION_URL="https://generativelanguage.googleapis.com/v1beta/openai/"
LLM_MODEL="gemini-2.0-flash"

Step 2: Install dependencies

uv is a fast Python package installer and resolver.

  1. Install uv, if not already installed:
pip install uv
  1. Create and activate a virtual environment:
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
  1. Install dependencies:
uv sync
  1. Start MCP Server:
uv run uvicorn mcp_server:mcp_app --reload
  1. Run the project with ChatAgent in CLI
uv run main.py
  1. Optionally start inspector
npx @modelcontextprotocol/inspector

Usage

Basic Interaction

Simply type your message and press Enter to chat with the model.

Document Retrieval

Use the @ symbol followed by a document ID to include document content in your query:

> Tell me about @deposition.md

Commands

Use the / prefix to execute commands defined in the MCP server:

> /summarize deposition.md

Commands will auto-complete when you press Tab.

Development

Adding New Documents

Edit the mcp_server.py file to add new documents to the docs dictionary.

Implementing MCP Features

To fully implement the MCP features:

  1. Complete the TODOs in mcp_server.py
  2. Implement the missing functionality in mcp_client.py

Linting and Typing Check

There are no lint or type checks implemented.

Quick Actions

Key Features

Model Context Protocol
Secure Communication
Real-time Updates
Open Source