octocode-mcp and snippy
These are complementary tools: octocode-mcp provides semantic code search across repositories via natural language queries, while snippy provides the infrastructure (Azure Functions, vector search, multi-agent orchestration) to build similar AI-powered code indexing and retrieval systems.
About octocode-mcp
bgauryy/octocode-mcp
MCP server for semantic code research and context generation on real-time using LLM patterns | Search naturally across public & private repos based on your permissions | Transform any accessible codebase/s into AI-optimized knowledge on simple and complex flows | Find real implementations and live docs from anywhere
This project helps software developers enhance their AI assistants by providing a comprehensive understanding of codebases. It takes code from GitHub, GitLab, and local repositories and processes it to allow AI assistants to perform tasks like code search, understanding implementations, and reviewing pull requests with deep context. This tool is for software engineers, tech leads, or engineering managers who want their AI assistants to operate with the expertise of a senior staff engineer.
About snippy
Azure-Samples/snippy
🧩 Build AI-powered MCP Tools with Azure Functions, Durable Agents & Cosmos vector search. Features orchestrated multi-agent workflows using OpenAI.
This project helps developers build intelligent tools that integrate with AI assistants like GitHub Copilot. It takes developer-friendly descriptions of desired functionality and creates serverless APIs that AI models can discover and use. Software architects and lead developers can use this to create robust, AI-powered systems.
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