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Alternatives to Linksee Memory

  • A
    license
    A
    quality
    B
    maintenance
    Gives your AI persistent memory across conversations. Stores facts automatically, finds them by meaning using hybrid search with query expansion, and organizes everything into topics without manual tagging.
    18
    1
    MIT

Related Servers

  • 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
  • F
    license
    Not graded
    quality
    C
    maintenance
    Local-first cross-agent memory for AI coding agents. Persistent, shared memory over MCP — what you tell one agent can be recalled by another — with all data stored in a single local SQLite file, no cloud and no API keys.
    -
  • A
    license
    A
    quality
    A
    maintenance
    Local-first persistent memory for coding agents and MCP clients. It keeps important project context across sessions and reduces wasted tokens by retrieving only relevant memories instead of replaying unnecessary history.
    8
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Local-first AI memory layer with hybrid retrieval and brain-inspired namespaces. Enables agents to save, search, and manage memories directly via MCP tools.
    5 npm
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    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.
    23
    39 PyPI
    15
    MIT

TDQS

A4.5/5.0

Scored across 8 tools

Disambiguation5/5

Each tool has a clear, distinct purpose: memory storage (remember), editing (update_memory), retrieval (recall, recall_file, list_entities), deletion/consolidation (forget, consolidate), and file caching (read_smart). There is no overlap that would cause misselection.

Naming Consistency4/5

Most tools follow a verb or verb_noun pattern (e.g., consolidate, forget, list_entities, recall, recall_file, remember, update_memory). 'read_smart' breaks this pattern with a verb_adjective form. Overall, the naming is mostly consistent with minor deviations.

Tool Count5/5

With 8 tools, the count is well within the ideal range for a memory management server. Each tool serves a necessary function without being redundant or excessive.

Completeness4/5

The tool set covers the core CRUD operations for memories, along with consolidation and file-specific retrieval. A direct 'get_memory_by_id' tool is missing, but recall can retrieve specific memories, so the gap is minor and workable.

Maintenance

ActivitySlowing
ResponsivenessNo issues