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Alternatives to Neotoma

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    Related Servers

    • A
      license
      Not graded
      quality
      F
      maintenance
      Local-first, auditable memory for AI agents. Provides durable context for MCP hosts with SQLite storage, CLI, and MCP tools for memory management.
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      Apache 2.0
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      Local-first, governable long-term memory for AI agents. Provides SQLite-backed storage, cross-session recall, and traceable memory corrections through a standard MCP interface.
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    • A
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      quality
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      Local-first, source-traceable memory for AI agents — no LLM at ingest, $0 per message, zero data egress. Gives Claude Code, Cursor, and any MCP client one shared persistent memory with semantic recall, belief revision, selective forgetting, and a provenance guard that blocks acting on stale or unconfirmed memories.
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    • A
      license
      A
      quality
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      A local-first shared memory layer for MCP-aware agents like Claude, Codex, and Hermes, enabling persistent memory across chats and clients via Markdown files and SQLite FTS.
      6
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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables any MCP client (zcode, Claude Code, Cursor) to give its model bi-temporal long-term memory, auditable evidence-cited retrieval, LLM-assisted document extraction, and deterministic A* skill planning with precondition/effect verification. All four capabilities share one portable SQLite store and can be mounted independently on demand.
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Cross-client AI memory hub for AI agents. Lets Claude Code, Cursor, Windsurf, and 20+ other clients share one physical SQLite memory database. Features bi-temporal time axes, source attribution, Q-Value usage-based ranking, and FTS5 full-text search with SQLite triggers.
      700 PyPI
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    TDQS

    C2.8/5.0

    Scored across 67 tools

    Disambiguation3/5

    Many tools overlap in purpose: retrieval is split across retrieve_entities, retrieve_entity_by_identifier, identify_entity_by_signals, retrieve_entity_snapshot, retrieve_related_entities, and retrieve_graph_neighborhood; writing/correcting across store, correct, correct_transaction, and patch_array_item; and generic vs issue-specific submission across submit_entity, submit_issue, add_entity_message, and add_issue_message. Detailed descriptions help, but the boundaries still require careful reading and invite misselection.

    Naming Consistency4/5

    Most tools follow a snake_case verb_noun pattern (list_observations, retrieve_entity_snapshot, create_relationship, delete_entity), with reasonable variety among verbs like get, list, and retrieve. Minor deviations include single-word imperative tools (store, correct, subscribe) and noun-first names (neotoma_turn_summary, npm_check_update, health_check_snapshots), but the overall convention remains readable and predictable.

    Tool Count1/5

    With 67 tools, the surface is far beyond the typical 3-15 range and qualifies as an extreme mismatch according to the rubric. Even for a complex knowledge-graph platform, this volume creates selection overhead and makes it hard for an agent to hold the whole toolset in working memory.

    Completeness4/5

    The server covers a broad lifecycle: storing, correcting, deleting, and restoring entities; managing schemas, relationships, observations, provenance, submissions, subscriptions, peers, bundles, and issues. Some gaps remain, such as resolve_sync_conflict being an explicit stub and no direct update_relationship operation, but core workflows are otherwise well supported.

    Maintenance

    ActivityActive
    ResponsivenessResponsive