Ollama MCP Server
Related Servers
Alternatives to Ollama MCP Server
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceA beginner-friendly MCP server that exposes a local Ollama model as an MCP tool, enabling users to ask questions via VS Code.-
- AlicenseNot gradedqualityBmaintenanceSelf-hosted MCP server using Ollama for local AI-powered code analysis, refactoring, and optimization. Integrates with VS Code via Continue or Roo.MIT
- AlicenseNot gradedqualityCmaintenanceA universal server that enables MCP-compatible clients (like Claude Desktop, Cursor, VS Code) to access OpenAI's APIs for chat completions, image generation, embeddings, and model listing through a standardized interface.7 npm7MIT
- AlicenseCqualityDmaintenanceA privacy-first MCP server that provides local LLM-enhanced tools for code analysis, security scanning, and automated task execution using backends like Ollama and LM Studio. It enables symbol-aware code reviews and workspace exploration while ensuring that all code and analysis remain strictly on your local machine.36ISC
- AlicenseNot gradedqualityAmaintenanceA Python MCP server that exposes local Ollama models as tools for AI assistants, enabling chat, generation, embeddings, and model management without cloud APIs.50 PyPI5MIT
- AlicenseNot gradedqualityBmaintenanceMCP server for delegating coding tasks to local Ollama models. Supports listing models and executing tasks with file writing capabilities.758 npmAGPL 3.0
TDQS
Scored across 6 tools
Tools are mostly distinct: model management (list, info, pull, delete) is clearly separated from inference (chat, generate). The only potential overlap is chat vs. generate, but chat is for multi-turn conversations while generate is for single completions, which is a standard distinction.
Most tools follow a verb_noun pattern (list_models, get_model_info, pull_model, delete_model), but chat and generate are single verbs without a noun object. This is a noticeable deviation, though the naming remains readable and understandable.
Six tools is well-scoped for an Ollama server, covering both model management and inference without unnecessary overlap or bloat. Each tool serves a clear purpose.
The toolset covers core lifecycle (list, info, pull, delete) and both chat and text generation. It lacks advanced features like model creation, copying, or embeddings, but these are not essential for basic Ollama interactions and can be added later.