Skip to main content
Glama
vornicx

midas-memory-mcp

by vornicx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to midas-memory-mcp

No user-submitted related servers found.

    Related Servers

    • Remnic

      joshuaswarren
      A
      license
      Not graded
      quality
      A
      maintenance
      Local-first memory for AI agents: one store shared by Claude Code, Codex CLI, Cursor, Pi, Hermes, OpenClaw, and any MCP client. Plain markdown with YAML frontmatter on your disk, hybrid BM25 + vector recall with per-result provenance (Recall X-ray), a correction contract, and the MemCorrect benchmark.
      211
      MIT
    • Memryzed by memryzed

      Memryzedofficial

      memryzed
      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.
      -

    • Talamus

      ampres-ai
      A
      license
      Not graded
      quality
      A
      maintenance
      Local-first, source-grounded memory for AI agents, with citations, bitemporal history, review-gated corrections, and MCP tools for search and recall.
      3
      Apache 2.0

    • Smriti

      moltizmo
      A
      license
      Not graded
      quality
      D
      maintenance
      Local-first persistent memory for AI agents via MCP, enabling semantic search and memory sharing across agents with zero cloud cost and full privacy.
      13 npm
      1
      MIT

    • auxly-memory-cli

      Tzamun-Arabia-IT-Co
      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
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.2/5.0

    Scored across 23 tools

    Disambiguation5/5

    Each tool targets a distinct memory operation: storage, retrieval, deletion, inspection, checks, context assembly, and commitment tracking. Detailed descriptions clearly differentiate similar-looking tools like recall, memory_state, and open_loops.

    Naming Consistency5/5

    Tools follow a consistent verb_noun pattern in snake_case (e.g., check_forbidden_action, remember_code). Single-word verbs like capture and maintain are exceptions but still clear and predictable within the naming convention.

    Tool Count5/5

    23 tools is a reasonable number for a comprehensive memory MCP server. Each tool serves a specific and justified purpose, covering storage, retrieval, maintenance, auditing, and checks without redundancy.

    Completeness5/5

    The tool surface covers the full memory lifecycle: creation (remember, capture), retrieval (recall, memory_state, project_state), deletion (forget, forget_all, forget_matching), maintenance (maintain, memory_policy), and auditing (audit_use, stats). Missing update is handled via supersession, and additional features like context assembly (build_context, resume) and conflict detection (memory_conflicts) round out the set.

    Maintenance

    ActivityStale
    ResponsivenessSlow

    Resources