Notebook Intelligence (NBI) is an AI coding assistant and extensible AI framework designed for JupyterLab. It supports models from GitHub Copilot and other LLM providers, including local Ollama models. It significantly enhances productivity through features such as code generation, auto - completion, and chat interfaces, and supports the integration of Model Context Protocol (MCP) services.

The StrawHat AI development repository provides a complete solution for building local and online AI development environments, including various tools such as the Ollama backend, Open - WebUI frontend, and Claude desktop proxy, supporting rapid deployment and development of AI applications.

An interactive chat assistant that combines the capabilities of the Ollama large - model and PostgreSQL database access, supporting natural language querying of databases and generating SQL queries.

This project is a deep research server based on the Ollama local large - model, providing automated research tools through the MCP protocol, capable of iterative search, analysis, and summarization of complex topics.

A deep research MCP service based on Ollama, realizing automated web search and knowledge synthesis through local LLM models

This project is an experimental Model Context Protocol (MCP) server for interacting with the Algolia API. It allows users to perform operations such as searching, adding data, and updating index configurations through the MCP protocol. The project provides installation guides, debugging methods, and instructions for integrating with Ollama, but clearly states that it does not provide official support.

The Deepseek Thinker MCP Server is an MCP service that provides Deepseek inference content, supporting both the OpenAI API and the local Ollama mode, and can be integrated into AI clients.

OtterBridge is a lightweight MCP server used to connect applications with multiple large language model providers, supporting models such as Ollama, with a simple and flexible design.

The Multi-Model Advisor is a multi - model consulting server based on Ollama, which provides more comprehensive answers to questions by integrating the viewpoints of multiple AI models.

A Model Control Protocol server designed for Claude Desktop to communicate with the Ollama LLM server

This project is a Python adapter that exposes the tools of MCPO (MCP-to-OpenAPI proxy server) as Ollama-compatible functions, supporting connection to existing MCPO instances or starting a local service.

Ollama Chat with MCP is a project that demonstrates how to integrate a local language model with real-time web search functionality through the Model Context Protocol (MCP). It includes an MCP web search server, a terminal client, and a Gradio-based web front-end, enabling locally run LLMs to access external tools and data sources.

MCP LLM Bridge is a bridge tool to connect the Model Context Protocol (MCP) server with OpenAI-compatible LLMs (such as Ollama).

File Context MCP is a TypeScript-based application that provides an API to query large language models (LLMs) through local file content. It supports multiple LLM providers (Ollama and Together.ai) and can process multiple file types to generate context-aware responses.

Ollama MCP Server is a protocol server that connects local Ollama LLM models with MCP - compatible applications, providing functions such as model management and conversation interaction.

A Model Context Protocol server for integrating Ollama with MCP clients such as Claude Desktop

The Ollama MCP Server is a bridge tool that connects the local large language models of Ollama and the Model Context Protocol (MCP). It provides complete API integration, model management, and execution functions, and supports OpenAI - compatible chat interfaces and visual multimodal models.

Nano Agent is an experimental small engineering proxy MCP server that supports multi-provider LLM models, used to test and compare the proxy capabilities of cloud and local LLMs in terms of performance, speed, and cost. The project includes a multi-model evaluation system, a nested agent architecture, and a unified tool interface, supporting providers such as OpenAI, Anthropic, and Ollama.

A RAG service based on the Qdrant vector database and Ollama/OpenAI embedding, providing document semantic search and management functions.

A TypeScript bridge project connecting local LLMs to MCP servers, providing a web interface that enables open-source models to use tool capabilities similar to Claude, supporting functions such as file system operations, web search, and complex reasoning.

The MCP Document Indexer is a Python - based local document indexing and search server that uses the LanceDB vector database and a local LLM (through Ollama) to implement real - time monitoring, multi - format document processing, and semantic search, and provides tools for AI assistants such as Claude through the Model Context Protocol (MCP).

Homelab MCP is a collection of Model Context Protocol servers used to manage and monitor home lab infrastructure through Claude Desktop. It supports multiple services such as Docker, Ollama, Pi-hole, Unifi, and UPS, and offers both unified and independent deployment modes.

This project implements the integration of the TypeScript MCP proxy with Ollama. Through a unified interface, AI models can call multiple tools, supporting functions such as file operations and web searches.

The Ollama MCP Server is a powerful bridge that seamlessly integrates Ollama with the Model Context Protocol (MCP), enabling Ollama's local LLM capabilities to be easily incorporated into MCP - driven applications.

The Multi-Model Advisor is a multi - model consulting system based on Ollama. It provides more comprehensive answers to questions by integrating different perspectives from multiple AI models. It uses the 'advisory board' model, allowing Claude to generate responses by synthesizing multiple AI perspectives.

The MCP RAG Server is a retrieval-augmented generation service based on the Model Context Protocol. It automatically indexes project documents through local tools (ChromaDB and Ollama) and provides context enhancement capabilities for connected LLMs.

The Local MCP Client is a cross - platform web and API interface tool that interacts with configurable MCP servers through natural language, supports local LLM models and Ollama, and enables structured tool execution and dynamic proxy behavior.

A Docker image project named Goose, integrated with the MCP server, supporting connection to LLM models through Ollama and adding GitHub MCP services via command - line extensions.

The Ollama-MCP-server is a protocol server that connects local Ollama LLM instances with MCP-compatible applications, providing functions such as task decomposition, result evaluation, and model management, and supporting standardized communication and performance optimization.

Tome is a MacOS application (support for Windows and Linux is coming soon) developed by the Runebook team. It aims to simplify the use of local large language models (LLMs) with MCP servers. By integrating Ollama and managing MCP servers, users can quickly start chatting with MCP-powered models without dealing with complex configurations.

The Unity MCP and Ollama integration package enables seamless communication between Unity and local large language models, supporting asset management and editor automation.

A semantic code search server based on the MCP protocol, supporting two embedding models, OpenAI and Ollama, capable of indexing local projects or Git repositories, and providing an enterprise - level private code search solution.

Ollama-MCP-server is a middleware server that connects the local Ollama large language model. It provides task decomposition, result evaluation, and model management functions through the Model Context Protocol, supporting standardized communication and performance optimization.

A Node.js-based vector search project that uses the LanceDB database and Ollama embedding model to implement document similarity search functionality

A lightweight client application based on the local OLLAMA model, integrating multiple MCP proxy tools through the BeeAI framework, providing a chat interface and database operation functions.

Node.js vector search implementation based on LanceDB and Ollama

An MCP server project based on the Ollama LLM model, providing Wikipedia article retrieval and summary generation functions, including a command-line client and a Streamlit web interface.

An AI code audit server based on the local Ollama model. Through the integration of the Model Context Protocol (MCP), it provides multi - dimensional code analysis, including security, integrity, performance, quality, architecture, testing, and documentation checks.

mcp - rag - server is a Retrieval Augmented Generation (RAG) server based on the Model Context Protocol (MCP). It provides relevant context for connected LLMs by indexing project documents. It uses ChromaDB and Ollama for local storage and embedding generation, supports multiple file formats, and can be quickly deployed using Docker.

A local multi-agent research system based on Ollama and BraveSearch, supporting tool calls and collaboration, suitable for AI research tasks.