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MCP server · Developer Tools

Ollama Agent

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..

51Fair

Scored 11 days ago · breakdown

About Ollama Agent

Ollama Agent is an MCP server published by ausboss in the Developer Tools category: 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..

The repository has 30 stars and 13 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/ausboss/mcp-ollama-agent

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

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I know everything about Ollama Agent. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

Static checks derived from the repository 4 days ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • !License declaredNo license file. Legally you have no right to use it in a product.
  • !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

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:

    • Node.js (version 18 or higher)

    • Ollama installed and running

    • Install the MCP tools globally that you want to use:

      # For filesystem operations
      npm install -g @modelcontextprotocol/server-filesystem
      
      # For web research
      npm install -g @mzxrai/mcp-webresearch
      
  2. Clone and install:

    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:

    {
      "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:

    npx tsx ./src/demo.ts
    
  5. Or start the chat interface with Ollama:

    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

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.

README fetched from the repository 4 days ago. The original is authoritative.

Questions

About Ollama Agent

How do I install Ollama Agent?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Ollama Agent safe to use with an AI agent?

Its trust score is 51 out of 100 (fair). It passes 3 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Ollama Agent still maintained?

The last commit was a year ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.