tifications. 3. Ensuring clients can use newly added tools immediately after registration. ## FAQ from Dynamic Tool MCP Server? - What is the purpose of the Dynamic Tool MCP Server? > It is designed to test MCP clients and their ability to manage tools dynamically. - How do I start the server? > You can start the server by running `npm start` after installing the dependencies. - Can I add my own tools? > Yes! You can use the `add_tool` command to dynamically add new tools to the server.26:T2a14,

A simple yet powerful Python client for interacting with Model Context Protocol (MCP) servers using Ollama, allowing local LLMs to use tools.

--- # MCP Client for Ollama (ollmcp) [![Python 3.10+](https://img.shields.io/badge/Python-3.10+-blue.svg)](https://www.python.org/downloads/) [![PyPI - Python Version](https://img.shields.io/pypi/v/ollmcp?label=ollmcp-pypi)](https://pypi.org/project/ollmcp/) [![PyPI - Python Version](https://img.shields.io/pypi/v/mcp-client-for-ollama?label=mcp-client-for-ollama-pypi)](https://pypi.org/project/mcp-client-for-ollama/) [![Build, Publish and Release](https://github.com/jonigl/mcp-client-for-ollama/actions/workflows/publish.yml/badge.svg)](https://github.com/jonigl/mcp-client-for-ollama/actions/workflows/publish.yml) [![CI](https://github.com/jonigl/mcp-client-for-ollama/actions/workflows/ci.yml/badge.svg)](https://github.com/jonigl/mcp-client-for-ollama/actions/workflows/ci.yml)

MCP Client for Ollama Demo

## Overview This project provides a robust Python-based client that connects to one or more Model Context Protocol (MCP) servers and uses Ollama to process queries with tool use capabilities. The client establishes connections to MCP servers, sends queries to Ollama models, and handles the tool calls the model makes. This implementation was adapted from the [Model Context Protocol quickstart guide](https://modelcontextprotocol.io/quickstart/client) and customized to work with Ollama, providing a user-friendly interface for interacting with LLMs that support function calling. ## Features - 🌐 **Multi-Server Support**: Connect to multiple MCP servers simultaneously - 🚀 **Multiple Transport Types**: Supports STDIO, SSE, and Streamable HTTP server connections - 🎨 **Rich Terminal Interface**: Interactive console UI - 🖥️ **Streaming Responses**: View model outputs in real-time as they're generated - 🛠️ **Tool Management**: Enable/disable specific tools or entire servers during chat sessions - 🧠 **Context Management**: Control conversation memory with configurable retention settings - 🤔 **Thinking Mode**: Advanced reasoning capabilities with visible thought processes for supported models (deepseek-r1, qwen3) - 🔄 **Cross-Language Support**: Seamlessly work with both Python and JavaScript MCP servers - 🔍 **Auto-Discovery**: Automatically find and use Claude's existing MCP server configurations - 🎛️ **Dynamic Model Switching**: Switch between any installed Ollama model without restarting - 💾 **Configuration Persistence**: Save and load tool preferences between sessions - 📊 **Usage Analytics**: Track token consumption and conversation history metrics - 🔌 **Plug-and-Play**: Works immediately with standard MCP-compliant tool servers - 🔔 **Update Notifications**: Automatically detects when a new version is available ## Requirements - **Python 3.10+** ([Installation guide](https://www.python.org/downloads/)) - **Ollama** running locally ([Installation guide](https://ollama.com/download)) - **UV package manager** ([Installation guide](https://github.com/astral-sh/uv)) ## Quick Start **Option 1:** Install with pip and run ```bash pip install ollmcp ollmcp ``` **Option 2:** One-step install and run ```bash uvx ollmcp ``` **Option 3:*

#tool-management

Dynamic Tool MCP Server

MCP Client for Ollama (ollmcp)