"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.

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

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.

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.

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

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

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.

Enables local document Q&A by reading .txt or .pdf files and answering questions in Persian using locally running models.

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

Enables consulting with local Ollama models for reasoning from alternative viewpoints. Supports sending prompts to Ollama models and listing available models on your local Ollama instance.

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.

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

Enables semantic search over local markdown specs, RFCs, and docs using Ollama and LanceDB, allowing AI agents to find relevant information by meaning rather than exact keywords.

Python MCP server for vector search using Qdrant vector database and Ollama embeddings, with advanced query techniques like query expansion, HyDE, and reranking.

Zero-trust, air-gapped Enterprise GraphRAG MCP server. Build knowledge graphs from local documents and run multi-hop, citation-grounded queries entirely offline with Ollama.

Persistent semantic memory for AI agents. SQLite-backed, local-first, zero config. Semantic search via Ollama embeddings with keyword fallback. Tools: remember, recall, history, forget, stats.

Enables indexing and semantic search of codebases and documents via MCP, using Ollama embeddings and Qdrant vector store.

An MCP server that queries multiple Ollama models and combines their responses, providing diverse AI perspectives on a single question for more comprehensive answers.