Skip to main content
Glama
moorcheh-ai

Memanto MCP

by moorcheh-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Related Servers

Alternatives to Memanto MCP

No user-submitted related servers found.

    Related Servers

    • Memento

      JoyciAkira
      A
      license
      C
      quality
      A
      maintenance
      Memento is a local-first, open-source MCP middleware that gives AI agents persistent memory, proactive goal enforcement, and autonomous intelligence using a SQLite temporal graph with Reciprocal Rank Fusion retrieval.
      15
      1
      AGPL 3.0

    • BuildAutomata Memory MCP

      brucepro
      F
      license
      Not graded
      quality
      D
      maintenance
      Provides AI agents with persistent, searchable memory that survives across conversations using semantic search, temporal versioning, and smart organization. Enables long-term context retention and cross-session continuity for AI assistants.
      14
      -

    • Tideline agent Memory

      ennisaaaaaaaa-stack
      F
      license
      Not graded
      quality
      B
      maintenance
      A long-term memory system built for AI Agents. Agent wakes up already knowing who he is, not querying "who am I?" every session. Every turn calling back accurate memory context. Achieving accurate memory hits while also preventing memory from expanding at scale. No compression, no forgetting.
      36
      -
    • Mnemexa MCP by mnemexa

      Mnemexa MCPofficial

      mnemexa
      A
      license
      A
      quality
      D
      maintenance
      Provides persistent, self-optimizing memory for AI agents, enabling them to remember preferences and context across sessions and share knowledge across multiple agents.
      4
      2 npm
      ISC

    • memex

      ayushagrawal288
      A
      license
      A
      quality
      C
      maintenance
      A production-grade persistent memory service for AI agents. Agents forget everything between sessions by default — memex fixes that. It stores, retrieves, and ranks conversation memory using semantic search with recency decay, so agents surface what's relevant and recent, not just what's semantically closest.
      4
      1
      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

    A4.1/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool serves a clearly distinct purpose: remember for single storage, batch_remember for bulk storage, and the recall variants cover different retrieval modes (semantic, recent, point-in-time, changed-since). The 'answer' tool adds a synthesis layer that is distinct from raw retrieval. No two tools appear to do the same thing.

    Naming Consistency5/5

    All tool names are lowercase with underscores, following a consistent verb-first convention. The recall_* family is uniformly prefixed, and remember/batch_remember are clearly related. The naming is predictable and intuitive.

    Tool Count5/5

    Seven tools is well-scoped for a memory server, covering storage and retrieval without bloat. Each tool earns its place, and the count sits comfortably in the ideal 3-15 range.

    Completeness3/5

    The tool surface covers creating and reading memories thoroughly, but lacks update and delete operations. Agents cannot correct a wrong memory or remove outdated information, which is a notable gap for a memory system. The absence of these lifecycle operations may cause dead ends in real use.

    Maintenance

    ActivityActive
    ResponsivenessSlow

    Resources