octocode-mcp and codeweaver
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 codeweaver
knitli/codeweaver
Semantic code search for AI agents — 166+ languages, hybrid search, works offline
Combines hybrid search (semantic vectors + AST parsing + keyword matching) with Reciprocal Rank Fusion for structural code understanding across 27 languages, backed by a 100% dependency-injection architecture that enables zero-code swapping between embedding providers (Voyage AI, FastEmbed, etc.) and vector stores. Includes automatic fallback to local FastEmbed when remote APIs timeout, circuit breaker patterns, and Pydantic boot-time validation for production reliability in airgapped environments.
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