MCPs tagged with codebase analysis
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In Memoria
Persistent memory and instant context for AI coding assistants, integrated via MCP.
In Memoria is an MCP server that enables AI coding assistants such as Claude or Copilot to retain, recall, and provide context about codebases across sessions. It learns patterns, architecture, and conventions from user code, offering persistent intelligence that eliminates repetitive explanations and generic suggestions. Through the Model Context Protocol, it allows AI tools to perform semantic search, smart file routing, and track project-specific decisions efficiently.
- ⭐ 94
- MCP
- pi22by7/In-Memoria
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Gitingest MCP Server
Turn any Git repository into a structured context for AI assistants via the Model Context Protocol.
Gitingest MCP Server provides a Model Context Protocol (MCP) compliant server that integrates with the gitingest tool to analyze and ingest Git repositories into structured text digests. It offers detailed repository analysis, including code summaries, file structures, and content extraction, tailored for integration with AI assistants. The server features flexible configuration and supports filtering by file size, patterns, and branches. It enables standardized delivery of codebase context to AI models for improved reasoning and comprehension.
- ⭐ 8
- MCP
- narumiruna/gitingest-mcp
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FileScopeMCP
Instantly understand and visualize your codebase structure & dependencies.
FileScopeMCP is a TypeScript-based server that implements the Model Context Protocol to analyze codebases, rank file importance, and track dependencies. It provides AI tools with comprehensive insights into file relationships, importance scores, and custom file summaries. The system supports visualization through Mermaid diagrams, persistent storage, and multi-language analysis for easier code comprehension. Seamless integration with Cursor ensures structured model context delivery for enhanced AI-driven code assistance.
- ⭐ 256
- MCP
- admica/FileScopeMCP