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Alternatives to wadachi

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    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP clients such as Claude Desktop, Cursor, Zed, and Windsurf to recall associative context from a folder of markdown notes, combining vector search entry points with one-hop [[wikilink]] graph expansion and cross-encoder reranking over a single SQLite file. It also appends a zero-token per-turn ledger of asks, files, tools, and decisions that agents can consult across sessions.
      242 PyPI
      13
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Local-first, file-based memory layer for AI agents — one shared Markdown vault across Claude, Codex, Gemini, Cursor and any MCP client. Provides read/write memory tools with an audit trail, per-agent trust levels, and Git sync; no cloud and no lock-in.
      2
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Local-first external brain for Claude Code, Codex, and any MCP client. Stores decisions, entities, and session artifacts in one SQLite file and exposes MCP tools for recall, page, promote, review, graph-query, and source-status.
      11
      4 npm
      6
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables coding agents to keep durable long-term memory in a folder of human-readable Markdown notes: search and read notes by ranked recall, encode new ones, link related ideas, retire contradicted notes in favor of replacements, and re-validate them — all backed by a disposable SQLite index. Plugs into Claude Code, Claude Desktop, Cursor, or any MCP client.
      7
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Gives every AI agent a shared, persistent memory by ingesting Obsidian vaults, code, transcripts, bookmarks and terminal sessions into a three-tier SQLite FTS5 store, then serving token-optimized hybrid retrieval, classification, promotion and cross-source synthesis over MCP and REST. This lets multiple agents read from and write to one compounding brain so each session starts with better context than the last.
      14 npm
      MIT

    TDQS

    B3.3/5.0

    Scored across 31 tools

    Disambiguation2/5

    Multiple tools overlap in purpose: recall, recall_associative, and related_memories all surface related memories with subtle differences. Similarly, sleep and consolidate both propose merge candidates, and review_procedures overlaps with housekeeping. The boundaries are not always clear despite descriptions.

    Naming Consistency2/5

    Many tools follow verb_noun (store_memory, get_memory, delete_memory), but there are inconsistent outliers like why, as_of, sleep, reflect, brain_status, memory_graph, and recall_associative. The mixed conventions make the set feel unpatterned and harder to predict.

    Tool Count2/5

    At 31 tools, the server is well over the typical well-scoped range (3-15). While the memory domain is broad, several tools could be consolidated (e.g., sleep and consolidate, recall and recall_associative), making the surface feel bloated rather than focused.

    Completeness3/5

    Memory CRUD is fully covered, and advanced features like belief tracking, insights, and graph operations are present. However, decisions lack update/delete operations, projects lack update/delete, and list_memories does not filter by tags. These gaps create dead ends for secondary entities.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues