"Information about Ollama" matching MCP servers:

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

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.

Enables Claude Code to leverage local Ollama models for tasks like summarizing large files, reviewing diffs, semantic code search, and generating boilerplate or tests, while also supporting a fully offline mode.

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

An MCP server that lets Claude Code delegate coding tasks such as code generation, review, refactoring, and test writing to a local Ollama instance running a Qwen3 model.

A minimal local vision bridge for text-only VS Code Copilot, enabling it to see images by sending them to a local Ollama vision model and returning text descriptions. It provides MCP tools for image description, listing, OCR, and status checks.

Exposes a local Ollama fleet as MCP tools for Claude Code, enabling model listing, generation, fleet health checks, parallel comparisons, smart host routing, and model pulling across hosts.

Enables users to retrieve and structure shipment tracking information from DB Schenker's website using natural language queries.

Enables web search and page content extraction through Ollama Cloud's APIs, including a combined search-and-fetch tool, with retries, timeouts, and safe error handling for MCP clients.

A Python MCP server that gives vision capabilities to text-only LLMs by exposing an analyze_image tool that sends local images to a vision-capable Ollama model and returns textual descriptions.

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.

Gives AI agents a persistent vector memory by embedding text with Ollama and storing it in Qdrant, so they can save, batch-save, semantically search with payload filters, and delete memories across collections.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.

MCP server enabling LLM clients without vision capability to process images by delegating to local Ollama vision models. Supports describing images, OCR, asking questions, and processing clipboard images.

Connects MCP-compatible coding agents to VMware vCenter to query information about virtual machines, hosts, clusters, datastores, datacenters, and networks.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

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

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 storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.

Enables Google Antigravity CLI to offload token-heavy workloads to local Ollama models through MCP tools for code drafting, summarization, chunked map-reduce, and JSON extraction, reducing cloud token usage.

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

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.

Allows to retrieve information about an AnnData object via MCP using the read_lazy function from anndata.

MCP server exposing web_search, web_fetch, and cluesift_domain_fetch tools with configurable Ollama API keys and HTTP or stdio transport.

Enables searching and retrieving information about anime, manga, and related content via the Bangumi API.

MCP server that transparently routes Ollama Cloud API requests across multiple user-owned accounts, handling quota exhaustion, rate limits, and failures via automatic account rotation.

A Model Context Protocol server that provides natural language access to Cortex API, enabling users to query information about their system's structure and make faster decisions about services, incidents, and team responsibilities.

A Kubernetes management MCP server that provides interfaces for getting information about Kubernetes clusters, performing operations, monitoring status, and analyzing resources.

Self-hosted MCP server using Ollama for local AI-powered code analysis, refactoring, and optimization. Integrates with VS Code via Continue or Roo.