MCPHost 🤖

A CLI host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP). Currently supports both Claude 3.5 Sonnet and Ollama models.

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Overview 🌟

MCPHost acts as a host in the MCP client-server architecture, where:

• Hosts (like MCPHost) are LLM applications that manage connections and interactions
• Clients maintain 1:1 connections with MCP servers
• Servers provide context, tools, and capabilities to the LLMs

This architecture allows language models to:

• Access external tools and data sources 🛠️
• Maintain consistent context across interactions 🔄
• Execute commands and retrieve information safely 🔒

Currently supports:

• Claude 3.5 Sonnet (claude-3-5-sonnet-20240620)
• Any Ollama-compatible model with function calling support
• Google Gemini models
• Any OpenAI-compatible local or online model with function calling support

Features ✨

• Interactive conversations with support models
• Non-interactive mode for scripting and automation
• Script mode for executable YAML-based automation scripts
• Support for multiple concurrent MCP servers
• Tool filtering with allowedTools and excludedTools per server
• 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

Requirements 📋

• Go 1.23 or later
• For Claude: An Anthropic API key
• For Ollama: Local Ollama installation with desired models
• For Google/Gemini: Google API key (see https://aistudio.google.com/app/apikey)
• One or more MCP-compatible tool servers

Environment Setup 🔧

1. Anthropic API Key (for Claude):

export ANTHROPIC_API_KEY='your-api-key'

2. Ollama Setup:

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

ollama pull mistral

• Ensure Ollama is running:

ollama serve

You can also configure the Ollama client using standard environment variables, such as OLLAMA HOST for the Ollama base URL.

3. Google API Key (for Gemini):

export GOOGLE_API_KEY='your-api-key'

4. OpenAI compatible online Setup

• Get your api server base url, api key and model name

Installation 📦

go install github.com/mark3labs/mcphost@latest

Configuration ⚙️

MCP-server

MCPHost will automatically create a configuration file in your home directory if it doesn't exist. It looks for config files in this order:

• .mcphost.yml or .mcphost.json (preferred)
• .mcp.yml or .mcp.json (backwards compatibility)

Config file locations by OS:

• Linux/macOS: ~/.mcphost.yml, ~/.mcphost.json, ~/.mcp.yml, ~/.mcp.json
• Windows: %USERPROFILE%\.mcphost.yml, %USERPROFILE%\.mcphost.json, %USERPROFILE%\.mcp.yml, %USERPROFILE%\.mcp.json

You can also specify a custom location using the --config flag.

STDIO

The configuration for an STDIO MCP-server should be defined as the following:

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

Each STDIO 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
• allowedTools: (Optional) Array of tool names to include (whitelist)
• excludedTools: (Optional) Array of tool names to exclude (blacklist)

Note: allowedTools and excludedTools are mutually exclusive - you can only use one per server.

Server Side Events (SSE)

For SSE the following config should be used:

{
  "mcpServers": {
    "server_name": {
      "url": "http://some_jhost:8000/sse",
      "headers":[
        "Authorization: Bearer my-token"
       ]
    }
  }
}

Each SSE entry requires:

• url: The URL where the MCP server is accessible.
• headers: (Optional) Array of headers that will be attached to the requests

System-Prompt

You can specify a custom system prompt using the --system-prompt flag. The system prompt should be a JSON file containing the instructions and context you want to provide to the model. For example:

{
    "systemPrompt": "You're a cat. Name is Neko"
}

Usage:

mcphost --system-prompt ./my-system-prompt.json

Usage 🚀

MCPHost is a CLI tool that allows you to interact with various AI models through a unified interface. It supports various tools through MCP servers and can run in both interactive and non-interactive modes.

Interactive Mode (Default)

Start an interactive conversation session:

mcphost

Script Mode

Run executable YAML-based automation scripts:

# Using the flag
mcphost --script myscript.sh

# Direct execution (if executable and has shebang)
./myscript.sh

Script Format

Scripts combine YAML configuration with prompts in a single executable file:

#!/usr/local/bin/mcphost --script
# This script uses the container-use MCP server from https://github.com/dagger/container-use
mcpServers:
  container-use:
    command: cu
    args:
      - "stdio"
prompt: |
  Create 2 variations of a simple hello world app using Flask and FastAPI. 
  Each in their own environment. Give me the URL of each app

Script Features

• Executable: Use shebang line for direct execution
• YAML Configuration: Define MCP servers directly in the script
• Embedded Prompts: Include the prompt in the YAML
• Config Fallback: If no mcpServers defined, uses default config
• Tool Filtering: Supports allowedTools/excludedTools per server
• Clean Exit: Automatically exits after completion

Script Examples

See examples/scripts/ for sample scripts:

• example-script.sh - Script with custom MCP servers
• simple-script.sh - Script using default config fallback

Non-Interactive Mode

Run a single prompt and exit - perfect for scripting and automation:

# Basic non-interactive usage
mcphost -p "What is the weather like today?"

# Quiet mode - only output the AI response (no UI elements)
mcphost -p "What is 2+2?" --quiet

# Use with different models
mcphost -m ollama:qwen2.5:3b -p "Explain quantum computing" --quiet

Available Models

Models can be specified using the --model (-m) flag:

• Anthropic Claude (default): anthropic:claude-3-5-sonnet-latest
• OpenAI or OpenAI-compatible: openai:gpt-4
• Ollama models: ollama:modelname
• Google: google:gemini-2.0-flash

Examples

Interactive Mode

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

# Use OpenAI's GPT-4
mcphost -m openai:gpt-4

# Use OpenAI-compatible model
mcphost --model openai:<your-model-name> \
--openai-url <your-base-url> \
--openai-api-key <your-api-key>

Non-Interactive Mode

# Single prompt with full UI
mcphost -p "List files in the current directory"

# Quiet mode for scripting (only AI response output)
mcphost -p "What is the capital of France?" --quiet

# Use in shell scripts
RESULT=$(mcphost -p "Calculate 15 * 23" --quiet)
echo "The answer is: $RESULT"

# Pipe to other commands
mcphost -p "Generate a random UUID" --quiet | tr '[:lower:]' '[:upper:]'

Flags

• --anthropic-url string: Base URL for Anthropic API (defaults to api.anthropic.com)
• --anthropic-api-key string: Anthropic API key (can also be set via ANTHROPIC_API_KEY environment variable)
• --config string: Config file location (default is $HOME/.mcphost.yml)
• --system-prompt string: system-prompt file location
• --debug: Enable debug logging
• --max-steps int: Maximum number of agent steps (0 for unlimited, default: 0)
• --message-window int: Number of messages to keep in context (default: 40)
• -m, --model string: Model to use (format: provider:model) (default "anthropic:claude-sonnet-4-20250514")
• --openai-url string: Base URL for OpenAI API (defaults to api.openai.com)
• --openai-api-key string: OpenAI API key (can also be set via OPENAI_API_KEY environment variable)
• --google-api-key string: Google API key (can also be set via GOOGLE_API_KEY environment variable)
• -p, --prompt string: Run in non-interactive mode with the given prompt
• --quiet: Suppress all output except the AI response (only works with --prompt)
• --script: Run in script mode (parse YAML frontmatter and prompt from file)

Configuration File Support

All command-line flags can be configured via the config file. MCPHost will look for configuration in this order:

1. ~/.mcphost.yml or ~/.mcphost.json (preferred)
2. ~/.mcp.yml or ~/.mcp.json (backwards compatibility)

Example config file (~/.mcphost.yml):

# MCP Servers
mcpServers:
  filesystem:
    command: npx
    args: ["@modelcontextprotocol/server-filesystem", "/path/to/files"]

# Application settings
model: "anthropic:claude-sonnet-4-20250514"
max-steps: 20
message-window: 40
debug: false
system-prompt: "/path/to/system-prompt.json"

# API keys (can also use environment variables)
anthropic-api-key: "your-key-here"
openai-api-key: "your-key-here"
google-api-key: "your-key-here"

Note: Command-line flags take precedence over config file values.

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
• /quit: Exit the application
• Ctrl+C: Exit at any time

Global Flags

• --config: Specify custom config file location
• --message-window: Set number of messages to keep in context (default: 10)

Automation & Scripting 🤖

MCPHost's non-interactive mode makes it perfect for automation, scripting, and integration with other tools.

Use Cases

Shell Scripts

#!/bin/bash
# Get weather and save to file
mcphost -p "What's the weather in New York?" --quiet > weather.txt

# Process files with AI
for file in *.txt; do
    summary=$(mcphost -p "Summarize this file: $(cat $file)" --quiet)
    echo "$file: $summary" >> summaries.txt
done

CI/CD Integration

# Code review automation
DIFF=$(git diff HEAD~1)
mcphost -p "Review this code diff and suggest improvements: $DIFF" --quiet

# Generate release notes
COMMITS=$(git log --oneline HEAD~10..HEAD)
mcphost -p "Generate release notes from these commits: $COMMITS" --quiet

Data Processing

# Process CSV data
mcphost -p "Analyze this CSV data and provide insights: $(cat data.csv)" --quiet

# Generate reports
mcphost -p "Create a summary report from this JSON: $(cat metrics.json)" --quiet

API Integration

# Use as a microservice
curl -X POST http://localhost:8080/process \
  -d "$(mcphost -p 'Generate a UUID' --quiet)"

Tips for Scripting

• Use --quiet flag to get clean output suitable for parsing
• Combine with standard Unix tools (grep, awk, sed, etc.)
• Set appropriate timeouts for long-running operations
• Handle errors appropriately in your scripts
• Use environment variables for API keys in production

MCP Server Compatibility 🔌

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

Contributing 🤝

Contributions are welcome! Feel free to:

• Submit bug reports or feature requests through issues
• Create pull requests for improvements
• Share your custom MCP servers
• Improve documentation

Please ensure your contributions follow good coding practices and include appropriate tests.

License 📄

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

Acknowledgments 🙏

• Thanks to the Anthropic team for Claude and the MCP specification
• Thanks to the Ollama team for their local LLM runtime
• Thanks to all contributors who have helped improve this tool