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mcp-ollama-agent

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A TypeScript example showcasing the integration of Ollama with the Model Context Protocol (MCP) servers. This project provides an interactive command-line interface for an AI agent that can utilize the tools from multiple MCP Servers..

27 stars TypeScriptAI & Machine Learning Updated Nov 4, 2025
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Documentation

TypeScript MCP Agent with Ollama Integration

This project demonstrates integration between Model Context Protocol (MCP) servers and Ollama, allowing AI models to interact with various tools through a unified interface.

✨ Features

  • Supports multiple MCP servers (both uvx and npx tested)
  • Built-in support for file system operations and web research
  • Easy configuration through `mcp-config.json` similar to `claude_desktop_config.json`
  • Interactive chat interface with Ollama integration that should support any tools
  • Standalone demo mode for testing web and filesystem tools without an LLM

🚀 Getting Started

1. Prerequisites:

    bash
    # For filesystem operations
         npm install -g @modelcontextprotocol/server-filesystem
    
         # For web research
         npm install -g @mzxrai/mcp-webresearch

    2. Clone and install:

    bash
    git clone https://github.com/ausboss/mcp-ollama-agent.git
       cd mcp-ollama-agent
       npm install

    3. Configure your tools and tool supported Ollama model in `mcp-config.json`:

    json
    {
         "mcpServers": {
           "filesystem": {
             "command": "npx",
             "args": ["@modelcontextprotocol/server-filesystem", "./"]
           },
           "webresearch": {
             "command": "npx",
             "args": ["-y", "@mzxrai/mcp-webresearch"]
           }
         },
         "ollama": {
           "host": "http://localhost:11434",
           "model": "qwen2.5:latest"
         }
       }

    4. Run the demo to test filesystem and webresearch tools without an LLM:

    bash
    npx tsx ./src/demo.ts

    5. Or start the chat interface with Ollama:

    bash
    npm start

    ⚙️ Configuration

    • MCP Servers: Add any MCP-compatible server to the `mcpServers` section
    • Ollama: Configure host and model (must support function calling)
    • Supports both Python (uvx) and Node.js (npx) MCP servers

    💡 Example Usage

    This example used this model qwen2.5:latest

    code
    Chat started. Type "exit" to end the conversation.
    You: can you use your list directory tool to see whats in test-directory then use your read file tool to read it to me?
    Model is using tools to help answer...
    Using tool: list_directory
    With arguments: { path: 'test-directory' }
    Tool result: [ { type: 'text', text: '[FILE] test.txt' } ]
    Assistant:
    Model is using tools to help answer...
    Using tool: read_file
    With arguments: { path: 'test-directory/test.txt' }
    Tool result: [ { type: 'text', text: 'rosebud' } ]
    Assistant: The content of the file `test.txt` in the `test-directory` is:
    rosebud
    You: thanks
    Assistant: You're welcome! If you have any other requests or need further assistance, feel free to ask.

    System Prompts

    Some local models may need help with tool selection. Customize the system prompt in `ChatManager.ts` to improve tool usage.

    🤝 Contributing

    Contributions welcome! Feel free to submit issues or pull requests.

    Frequently asked questions

    What is mcp-ollama-agent?

    mcp-ollama-agent is A TypeScript example showcasing the integration of Ollama with the Model Context Protocol (MCP) servers. This project provides an interactive command-line interface for an AI agent that can utilize the tools from multiple MCP Servers..

    How do I install mcp-ollama-agent?

    Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

    Is mcp-ollama-agent open source?

    Yes — it is hosted on GitHub at https://github.com/ausboss/mcp-ollama-agent and has 27 stars.

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