MCPCLIHost

★ 22

from vincent-pli

A CLI host that allows Large Language Models (LLMs) to interact with external tools using the Model Context Protocol (MCP).

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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.

English | 简体中文

What it looks like: 🤠

snapshot

Features ✨

Interactive conversations with multipe LLM models
Support for multiple concurrent MCP servers
Dynamic tool discovery and integration
Configurable MCP server locations and arguments
Configurable message history window for context management
Monitor/trace error from server side
Support Sampling, Roots, Elicitation, retrievling Resource, Prompts
Support runtime exclude specific tool
Show MCP server card when connected
display image from tool call output

Latest Update 💌

[2025-11-26] Support display image from tool call output
[2025-07-18] Support Streamable HTTP mcp server, OAuth process not support yet
[2025-07-02] Support Elicitation
[2025-06-27] Deal with Prompts in MCP server: Link
[2025-06-20] Deal with Resources in MCP server: Link

MCP Server Compatibility 🔌

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

Copy & paste — that's it

pip install mcp-cli-host

Environment Setup 🔧

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

For Ollama, need setup firstly:

Install Ollama from https://ollama.ai
Pull your desired model:

ollama pull mistral

Ensure Ollama is running:

ollama serve

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'

For Google Gemini

export GEMINI_API_KEY='your-gemini-api-token'

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:

STDIO mcp server

{
  "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

Remote mcp server(only support Streamable HTTP)

{
  "mcpServers": {
    "github": {
      "url": "https://api.githubcopilot.com/mcp/",
      "headers": {"Authorization": "Bearer <your PAT>"}
    }
  }
}

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
Gemini: gemini:gemini-2.5-flash

Examples

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

# Use Deepseek
mcpclihost -m deepseek:deepseek-chat --sys-prompt 'You are a slightly playful assistant, please answer questions in a cute tone!'

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)
--roots string: MCP clients to expose filesystem “roots” to servers
--sys-prompt string: System prompt

Interactive Commands

While chatting, you can use:

/help: Show available commands
/tools: List all available tools
/exclude_tool tool_name: Exclude specific tool from the conversation
/resources: List all available resources
/get_resource: Get specific resources by uri, example: /get_resource resource_uri
/prompts: List all available prompts
/get_prompt: Get specific prompt by name, example: /get_prompt prompt_name
/servers: List configured MCP servers
/history: Display conversation history
/quit: Exit at any time