octocode-mcp and code-graph-context
These are complements that serve different stages of code analysis: semantic search across repositories versus deep structural understanding within a single codebase, so they would be used together when you need both broad code discovery and focused contextual analysis.
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 code-graph-context
andrew-hernandez-paragon/code-graph-context
A Model Context Protocol (MCP) server that builds rich code graphs to provide deep contextual understanding of TypeScript codebases to Large Language Models.
This project gives your AI coding assistant a complete, detailed understanding of your TypeScript codebase. It takes your existing TypeScript code and transforms it into a smart, interconnected map, allowing your AI to grasp how all parts of your system work together. Software developers can use this to make their AI coding assistants much more effective for complex tasks.
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