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    Provides MCP tools to search, compare, and get recommendations for open-source projects from a structured knowledge graph of GitHub data.
    MIT
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    Analytical memory for AI agents: a real Postgres your agent connects to over MCP and queries in plain English — GROUP BY, JOIN, aggregate over what it remembered, not just top-k vector recall.
    7
    2
    Functional Source , Version 1.1, ALv2 Future
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    Provides AI agents with persistent memory and knowledge management through a comprehensive knowledge graph platform. Enables storing, searching, and managing entities, relationships, and observations with advanced features like trending analysis and smart ranking.
    3
    MIT
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    A lightweight MCP sidecar exposing safe, read-only Anchor note tools to ChatGPT via a tunnel client in the same Docker stack. It currently supports listing, searching, reading notes, tags, and attachment metadata without exposing Anchor's private API or database.
    11 npm
    MIT
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    Serves AI clients on demand with atomic, provenance-tracked claims about your people, teams, systems and decisions, exposing search, open, timeline, correct and define tools so assistants can pull what is currently true rather than stale document fragments. It also lets clients correct or define knowledge in place, so retrieved facts stay accurate and reversible over time.
    MIT
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    Reads top-level sessions from Claude Code, Codex CLI, and Grok Build, filters and anonymizes them, then writes snapshots to Google Drive for mixed semantic search, portrait retrieval, and status queries.
    37 npm
    1
    Apache 2.0
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    Enables agents and users to keep a shared, append-only SQLite lab notebook across every project on a machine, recording pre-registered hypotheses with falsifiers, measurements, verdicts, and superseding questions. It exposes tools for checking where an investigation currently stands and for reviewing everything already ruled out before re-deriving it.
    MIT
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    Every memory framework treats a frequently-used fact as trustworthy forever but "still relevant" and "still true" aren't the same thing.A customer's city, a teammate's role, a project's status: these age quietly, and nothing catches it until an agent confidently repeats something that stopped being true months ago. FactLayer is a lightweight check that sits on top of whatever memory system you.
    1
    MIT
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    A local, read-only MCP server that lets agents see the page the user is currently on, how they arrived at it, their inferred intent, and what they have read before, drawing from a private on-machine ledger. It also supports full-text search over previously visited pages and returns relevant passages or full readable text instead of requiring copy-paste.
    9 npm
    1
    MIT
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    Provides AI agents with a persistent long-term memory over a single SQLite file, letting them write, screen, consolidate, and recall notes across sessions without any generative LLM in the loop. Recall judges relevance, follows links between notes, and signals when memory is insufficient, so agents get one to three useful facts per question instead of a generic top-k list.
    11
    26 PyPI
    2
    MIT
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    Enables AI agents to store decisions as a versioned history, linking each new decision to the one it replaces so that recall always resolves to the decision currently in force instead of obsolete ones. It runs fully locally on a single SQLite file with BM25 search, and can optionally detect replacements automatically via an LLM or heuristic linker.
    5
    MIT
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    Enables Codex to browse Bilibili content through read-only endpoints — anonymous trending candidates and hot comments, plus search, descriptions, subtitles, and danmaku summaries once a cookie is configured. It also maintains a local, deduplicated observation diary with persona preferences, timezone-based activity windows, and daily quotas for scheduling reading cycles.
    10
    1
    MIT
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    Enables AI clients and agents to turn a new idea into a structured set of clarifying questions, technology options, upward design breakdowns, reverse reasoning, and risk assessments so users can steer top-level design decisions. It also supports saving insights and building a bidirectional design tree of concepts and their implementations.
    19
    MIT