Skip to main content
Glama

MCP Chat

by Ramsi-K
README.md2.19 kB
# 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 ## 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: ``` ANTHROPIC_API_KEY="" # Enter your Anthropic API secret key ``` ### Step 2: Install dependencies #### Option 1: Setup with uv (Recommended) [uv](https://github.com/astral-sh/uv) is a fast Python package installer and resolver. 1. Install uv, if not already installed: ```bash pip install uv ``` 2. Create and activate a virtual environment: ```bash uv venv source .venv/Scripts/activate # On Windows: .venv\Scripts\activate ``` 3. Install dependencies: ```bash uv pip install -e . ``` 4. Run the project ```bash uv run main.py ``` #### Option 2: Setup without uv 1. Create and activate a virtual environment: ```bash python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate ``` 2. Install dependencies: ```bash pip install anthropic python-dotenv prompt-toolkit "mcp[cli]==1.8.0" ``` 3. Run the project ```bash 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: 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.

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Ramsi-K/mcp-chatbot-cli'

If you have feedback or need assistance with the MCP directory API, please join our Discord server