mcp-ollama-code-analyzer
Provides real-time code analysis, refactoring, and optimization using local LLMs via Ollama.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-ollama-code-analyzeranalyze this Python function for potential bugs and optimization"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🚀 MCP Ollama Code Analyzer
A self-hosted, privacy-focused alternative to GitHub Copilot. Uses Ollama (local LLMs) with MCP servers in Docker for real-time code analysis, refactoring, and optimization. Requires a CUDA-capable GPU for optimal performance.
📌 Features
✅ Local AI-powered code analysis (no cloud costs!)
✅ Dockerized MCP server (easy setup)
✅ VS Code integration (Continue/Roo)
✅ CUDA acceleration (for optimal performance)
✅ Supports multiple Ollama models (e.g., llama3, codellama)
✅ Real-time code improvements (refactoring, bug fixes, optimizations)
Related MCP server: LocalNest MCP
🛠️ Requirements
Docker & Docker Compose
NVIDIA Container Toolkit (for CUDA acceleration)
Ollama (locally installed)
CUDA-capable GPU (e.g., NVIDIA RTX 30xx/40xx, A100, etc.)
🚀 Quick Start
1. Clone the repository
git clone https://github.com/sikienzl/mcp-ollama-code-analyzer.git
cd mcp-ollama-code-analyzerThis server cannot be installed
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