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"A tool for storing and maintaining up-to-date codebase memory/context" matching MCP servers:

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    Enables LLM assistants to store, retrieve, and update user-specific context memory including travel preferences and general information through a chat interface. Provides analytics on tool usage patterns and token costs for continuous improvement.
    Last updated
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    Enables AI assistants to semantically search and understand code repositories using PostgreSQL with pgvector embeddings. Provides repository indexing, natural language code search, and development task management with git integration.
    Last updated
    MIT
  • A
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    Enables semantic search across your codebase using Google's Gemini embeddings and Qdrant Cloud vector storage. Supports 15+ programming languages with smart code chunking and real-time file change monitoring.
    Last updated
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    19
    MIT
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    Enables AI agents to semantically search and navigate code repositories using natural language, with support for multiple repos, incremental indexing, and no local install needed.
    Last updated
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    A minimalist indexing tool that provides AI agents with semantic search and structural AST parsing for deep codebase understanding. It enables autonomous agents to navigate large codebases predictably using vector embeddings and native language server capabilities like definition and reference tracking.
    Last updated
  • A
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
    Last updated
    3
    27
    Apache 2.0
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    Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.
    Last updated
    10
    MIT
  • A
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    An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.
    Last updated
    8
    MIT
  • A
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    A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.
    Last updated
    10
    MIT
  • A
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    Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.
    Last updated
    6
    6
    MIT
  • A
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    Provides persistent context management for AI agents by storing and querying semantic information using Upstash Vector DB and Google AI embeddings. It enables semantic search, batch operations, and metadata filtering to help agents retrieve relevant stored knowledge.
    Last updated
    6
    3
    MIT
  • A
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    A persistent memory MCP server for Claude Code that automatically saves conversations and retrieves relevant history across sessions to provide context.
    Last updated
    17
    11
    MIT