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    An MCP server that captures the rationale behind code changes at the moment they are written, binding decisions to commits with full provenance, and serves that context later without guessing. It records 'why code exists' and tracks anchor health over time.
    MIT
  • F
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    A
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    maintenance
    An AI conversation management layer that enables creating chat sessions, persisting message history to GitHub, and performing semantic searches over past interactions. It supports multi-turn threading and context injection to integrate external memory sources into Claude conversations.
    12
  • F
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    A composable semantic memory layer that provides cross-project recall and session context using Qdrant and OpenAI embeddings. It enables users to securely store, search, and manage persistent memories with built-in secret scrubbing for privacy.
    11
  • A
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    quality
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    TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.
    2
    Apache 2.0
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    license
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    quality
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    maintenance
    Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.
    6
    MIT
  • A
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    quality
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    maintenance
    Provides MCP tools to search, compare, and get recommendations for open-source projects from a structured knowledge graph of GitHub data.
    MIT
  • F
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    quality
    B
    maintenance
    Builds a personal knowledge graph from selected ChatGPT conversations (stored in Neo4j) and exposes it to Claude Code as an on-demand MCP search tool.
  • F
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    quality
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    maintenance
    A local MCP server that maintains a persona profile (contact library) for AI assistants, allowing them to create, search, retrieve, supplement, and correct information about people mentioned in conversations via tools like search_profiles, get_profile, create_profile, update_profile, add_facts, update_fact, and delete_fact.
    8
  • A
    license
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    quality
    A
    maintenance
    Git-native long-term memory for AI agents: your markdown files are the source of truth, the search index is a disposable projection rebuilt from git, and every memory the agent writes is a reviewable git commit. Served over one OAuth-secured MCP endpoint with hybrid lexical+semantic recall and a gated, git-first commit_note write tool.
    7
    8
    AGPL 3.0
  • A
    license
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    quality
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    maintenance
    Gives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.
    10
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    1
    MIT
  • A
    license
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    quality
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    maintenance
    A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep
    5
    1
    MIT