Model Context Protocol bulding client and servers
Overview
MCP Chat is a command-line interface application that enables interactive chat capabilities with AI models through the Anthropic API. The application supports document retrieval, command-based prompts, and extensible tool integrations via the MCP (Model Control Protocol) architecture. - Python 3.9+ - Anthropic API Key (I have used an OpenAI API key) 1. Create or edit the .env file in the project root and verify that the following variables are set correctly: uv is a fast Python package installer and resolver. 1. Install uv, if not already installed: 2. Create and activate a virtual environment: 1. Create and activate a virtual environment: Simply type your message and press Enter to chat with the model.
README
MCP Chat
MCP Chat is a command-line interface application that enables interactive chat capabilities with AI models through the Anthropic API. The application supports document retrieval, command-based prompts, and extensible tool integrations via the MCP (Model Control Protocol) architecture.
Prerequisites
- Python 3.9+
- Anthropic API Key (I have used an OpenAI API key)
Setup
Step 1: Configure the environment variables
- Create or edit the
.envfile in the project root and verify that the following variables are set correctly:
ANTHROPIC_API_KEY="" # Enter your Anthropic API secret key
Step 2: Install dependencies
Option 1: Setup with uv (Recommended)
uv is a fast Python package installer and resolver.
- Install uv, if not already installed:
pip install uv
- Create and activate a virtual environment:
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
- Install dependencies:
uv pip install -e .
- Run the project
uv run main.py
Option 2: Setup without uv
- Create and activate a virtual environment:
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
- Install dependencies:
pip install anthropic python-dotenv prompt-toolkit "mcp[cli]==1.8.0"
- Run the project
python main.py
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:
- Complete the TODOs in
mcp_server.py - Implement the missing functionality in
mcp_client.py
Linting and Typing Check
There are no lint or type checks implemented.
Install
This server does not publish a one-line install command.
Open the repository installation guide New to MCP? Start with the mcpskill.org guide →