"A server for local file operations on Windows that integrates with Ollama" matching MCP servers:

Hardened MCP bridge to the full Ollama ecosystem — local and cloud models. 6 tools covering health, model management, chat, and generation with SSRF mitigation, singleton HTTP client, and structured error handling. Two deps, one file.

MCP Ollama server integrates Ollama models with MCP clients, allowing users to list models, get detailed information, and interact with them through questions.

A bridge that integrates Ollama's local LLM capabilities into MCP-powered applications, enabling users to run, manage, and interact with AI models locally with full control and privacy.

A bridge that enables Claude Code to interact with local Ollama instances for text generation, multi-turn chat, and vision-based analysis. It supports model management tasks such as listing, pulling, and showing details, alongside generating text embeddings.

Provides tools for searching and reading local files, supporting metadata filters, PDF full-text keyword search, and sandboxed file access.

Enables seamless integration between Ollama's local LLM models and MCP-compatible applications, supporting model management and chat interactions.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

This is a Model Context Protocol (MCP) server adaptation of LangChain Ollama Deep Researcher. It provides the deep research capabilities as MCP tools that can be used within the model context protocol ecosystem, allowing AI assistants to perform in-depth research on topics (locally) via Ollama

A comprehensive MCP proxy server that bridges MCP clients with Ollama local language models, providing advanced features like RAG integration, context management, caching, and production-ready security.

Exposes local Ollama instances as tools for Claude Code, allowing users to offload code generation, text drafting, and embedding tasks to local GPUs. It supports multi-turn conversations and model management through the Model Context Protocol.

Bridges Ollama's capabilities with MCP-compatible clients, enabling web search and content fetching to provide real-time information and reduce hallucinations.

Provides direct access to Ollama models for AI inference, including text generation, chat, model management, and embeddings.

A multi-agent operations assistant that answers business questions by searching local documents and order records.

Enables AI assistants to perform semantic search and retrieval across codebases stored in Qdrant, using Ollama models for GPU-accelerated embeddings.

Local-first temporal knowledge graph with six read-only MCP retrieval tools. Supports Ollama and embedded LadybugDB; additions use a separate CLI proposal queue with human approval and explicit application.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

Enables read-only semantic search over a local document corpus with on-device embeddings and a local Chroma store, featuring symlink-hardened file access and structured error handling.

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

Enables LLM clients to query local markdown engineering documentation by indexing files into ChromaDB with Ollama embeddings and exposing a search_internal_docs tool over stdio, all offline and privacy-first.

An interactive chat interface that combines Ollama's LLM capabilities with PostgreSQL database access through the Model Context Protocol (MCP). Ask questions about your data in natural language and get AI-powered responses backed by real SQL queries.