"Information about Ollama" matching MCP servers:

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Enables AI agents to offload mechanical, high-token work to local Ollama models through MCP, with role-based model discovery, batch processing, and file-aware inputs.

Routes AI tasks to appropriate local LLM models (quick, coder, MoE, thinking) with automatic model selection, multi-backend support (Ollama, llama.cpp, Gemini), and parallel processing capabilities.

Offloads cheap work from cloud LLM agents to a local Ollama model, reducing costs and keeping frontier models focused on complex tasks.

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.

Simulates harsh, fake user reviews to psychologically condition AI agents for enforcing disciplined development practices, with optional Ollama integration for dynamic criticism.

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.

Enables AI agents to interact with local Ollama models for text generation and tool calling with prompt injection protection.

A lightweight MCP server that provides a unified interface to various LLM providers including OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama.

Enables complete local Ollama management including listing models, chatting with local LLMs, starting/stopping the server, and getting intelligent model recommendations for specific tasks through natural language commands.

An AI router that connects applications to multiple LLM providers (OpenAI, Anthropic, Google, DeepSeek, Ollama, etc.) with smart model orchestration capabilities, enabling dynamic switching between models for different reasoning tasks.

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.

Provides reasoning content to MCP-enabled AI clients by interfacing with Deepseek's API or a local Ollama server, enabling focused reasoning and thought process visualization.

Analyzes log files locally using Ollama and files structured GitHub Issues automatically, with all processing kept on your machine.

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.

Enables collaboration with multiple AI providers (Claude, GPT-4, Gemini, Ollama) directly from VS Code with automatic project context injection and persistent conversation history. Provides streamlined tools for getting AI advice, multi-provider research, and enhanced context sharing across sessions.

Enables AI agents to inspect and free NVIDIA GPU VRAM by managing Ollama models, helping make room for loading new models.

Enables a local-first autonomous coding agent that plans, edits, and verifies code using LM Studio, Ollama, or llama.cpp models, with hardware-aware parallel sub-agents and optional frontier-model planning.

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.

GUI automation MCP server that enables AI agents to see and control the Windows desktop using a local Vision LLM (Ollama), supporting screenshot analysis, mouse/keyboard actions, and autonomous task execution.