Skip to main content
Glama
Sign In
MCP-Memory-LanceDB-Pro

MCP-Memory-LanceDB-Pro

by bcornish1797
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Related Servers

Alternatives to MCP-Memory-LanceDB-Pro

No user-submitted related servers found.

    Related Servers

    • MemoVault

      Blvckjs96
      A
      license
      A
      quality
      D
      maintenance
      A personal memory system that provides AI assistants with long-term memory capabilities through semantic search and vector storage. It enables Claude Code to store, retrieve, and manage personal context and project preferences using flexible LLM backends.
      8
      MIT

    • open-mem

      kamalivaturi
      A
      license
      Not graded
      quality
      C
      maintenance
      Gives Claude Code a persistent, fully local long-term memory by automatically capturing session activity, indexing past conversations, projects, scheduled tasks and Obsidian notes, and recalling relevant context through hybrid keyword-plus-semantic search with progressive disclosure. It also writes session handoffs that are injected into later sessions, so work resumes with prior decisions and next steps already in context.
      58 npm
      Apache 2.0
    • PseudoLife-MCP

      PseudoLife-MCPofficial

      Pseudogiant-xr
      A
      license
      A
      quality
      B
      maintenance
      Enables persistent long-term memory for Claude Code across sessions, with tools for storing, searching, and managing facts, knowledge graphs, and procedural lessons.
      38
      1,774 PyPI
      6
      Apache 2.0

    • SuperMemory

      Yuziki1227
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables Claude Code and Codex to write, update, and retrieve durable long-term memories that survive session boundaries and context compaction. All recall runs locally against a single SQLite file using hybrid BM25, embedding, and recency ranking cut to an explicit token budget, with no cloud dependency.
      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 14 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: memory operations (store, list, recall, update, forget, etc.) and self-improvement logging are separate concerns. No ambiguity between tools.

    Naming Consistency5/5

    All tools follow a consistent snake_case pattern with `memory_` or `self_improvement_` prefix, making predictable verb/noun structure throughout.

    Tool Count5/5

    14 tools is well-scoped for a memory management server, covering core operations and advanced features like decay and reflection without being excessive.

    Completeness5/5

    CRUD operations are fully covered, plus advanced features (decay, reflection, migration, statistics) and self-improvement logging. No obvious gaps for the domain.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

    Resources