MCPCLIHost 🤖

A CLI host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP). Currently supports Openai, Azure Openai, Deepseek and Ollama models.

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What it looks like: 🤠

https://github.com/vincent-pli/mcp-cli-host/blob/main/mcp-cli-host.png

Features ✨

- Interactive conversations with multipe LLM models
- Support for multiple concurrent MCP servers
- Dynamic tool discovery and integration
- Tool calling capabilities for both model types
- Configurable MCP server locations and arguments
- Consistent command interface across model types
- Configurable message history window for context management
- Monitor/trace error from server side
- Support sampling
- Support Roots

Environment Setup 🔧

1. For Openai and Deepseek:

export OPENAI_API_KEY='your-api-key'

By default for Openai the base_url is "https://api.openai.com/v1"
For deepseek it's "https://api.deepseek.com", you can change it by --base-url

2. For Ollama, need setup firstly:
- Install Ollama from https://ollama.ai
- Pull your desired model:

ollama pull mistral

- Ensure Ollama is running:

ollama serve

3. For Azure Openai:

export AZURE_OPENAI_DEPLOYMENT='your-azure-deployment'

export AZURE_OPENAI_API_KEY='your-azure-openai-api-key'

export AZURE_OPENAI_API_VERSION='your-azure-openai-api-version'

export AZURE_OPENAI_ENDPOINT='your-azure-openai-endpoint'

Installation 📦

pip install mcp-cli-host

Configuration ⚙️

MCPCLIHost will automatically find configuration file at ~/.mcp.json. You can also specify a custom location using the --config flag:

{
  "mcpServers": {
    "sqlite": {
      "command": "uvx",
      "args": [
        "mcp-server-sqlite",
        "--db-path",
        "/tmp/foo.db"
      ]
    },
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/tmp"
      ]
    }
  }
}

Each MCP server entry requires:
- command: The command to run (e.g., uvx, npx)
- args: Array of arguments for the command:
- For SQLite server: mcp-server-sqlite with database path
- For filesystem server: @modelcontextprotocol/server-filesystem with directory path

Usage 🚀

MCPCLIHost is a CLI tool that allows you to interact with various AI models through a unified interface. It supports various tools through MCP servers.

Available Models

Models can be specified using the --model (-m) flag: - Deepseek: deepseek:deepseek-chat - OpenAI: openai:gpt-4 - Ollama models: ollama:modelname - Azure Openai: azure:gpt-4-0613

Examples

# Use Ollama with Qwen model
mcpclihost -m ollama:qwen2.5:3b
Use Deepseek
mcpclihost -m deepseek:deepseek-chat

Flags

- --config string: Config file location (default is $HOME/mcp.json) - --debug: Enable debug logging - --message-window int: Number of messages to keep in context (default: 10) - -m, --model string: Model to use (format: provider:model) (default "anthropic:claude-3-5-sonnet-latest") - --base-url string: Base URL for OpenAI API (defaults to api.openai.com)

Interactive Commands

While chatting, you can use:
- /help: Show available commands
- /tools: List all available tools
- /servers: List configured MCP servers
- /history: Display conversation history
- Ctrl+C: Exit at any time

MCP Server Compatibility 🔌

MCPCliHost can work with any MCP-compliant server. For examples and reference implementations, see the MCP Servers Repository.

License 📄

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.