Skip to main content
Glama
Scofieldkoh

AI Memory MCP Server

by Scofieldkoh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

Related Servers

Alternatives to AI Memory MCP Server

No user-submitted related servers found.

    Related Servers

    • Simple Memory MCP Server

      AojdevStudio
      F
      license
      A
      quality
      D
      maintenance
      A lightweight MCP server that provides persistent knowledge graph storage for AI assistants, enabling memory across sessions through entity-relationship storage with JSON file persistence.
      10
      1
      -

    • Local Brain MCP

      ejsinfuego
      F
      license
      Not graded
      quality
      D
      maintenance
      A local MCP server for AI assistants to store and retrieve personal memories on disk, with optional semantic search using embeddings.
      -

    • Memento

      Kotrotsos
      A
      license
      A
      quality
      D
      maintenance
      A persistent memory MCP server for AI assistants, storing and retrieving notes using local JSONL files with BM25 search.
      5
      MIT

    • Memento

      iAchilles
      A
      license
      A
      quality
      C
      maintenance
      A local, fully-offline MCP memory server that enables persistent storage and retrieval of information using SQLite with both keyword and semantic vector search capabilities.
      10
      19 npm
      13
      MIT

    • saor-mcp

      ubajxn
      A
      license
      A
      quality
      C
      maintenance
      MCP server providing persistent memory for AI agents, enabling them to read, write, and query memories across sessions.
      9
      4 npm
      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

    A3.7/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: clear_memories removes all memories, delete_memory targets a specific ID, get_memory_stats provides metadata, list_memories enumerates with filtering, search_memories finds matches based on content, and store_memory adds new data. An agent can easily distinguish between these operations.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., clear_memories, delete_memory, store_memory). The verbs are precise and descriptive, making the set highly predictable and readable.

    Tool Count5/5

    With 6 tools, the server is well-scoped for an AI memory management system. Each tool serves a distinct role in the memory lifecycle (store, retrieve, search, manage, and analyze), and none feel redundant or missing for the domain.

    Completeness5/5

    The toolset provides complete CRUD/lifecycle coverage for memory management: store_memory (create), list_memories/search_memories (read/query), delete_memory (delete), clear_memories (bulk delete), and get_memory_stats (analytics). There are no obvious gaps that would hinder an agent's workflow.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources