Skip to main content
Glama
liza-studio

skillmem

by liza-studio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to skillmem

  • basic-memory

    basicmachines-co
    A
    license
    B
    quality
    A
    maintenance
    Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data. Integrates directly with Obsidan.md
    17
    5,691 PyPI
    3,970
    AGPL 3.0

Related Servers

  • Engram Alpha

    lalithbuilds
    A
    license
    B
    quality
    A
    maintenance
    Enables local AI coding agents and web agents to store, retrieve, and search memories using hybrid semantic, lexical, and knowledge-graph ranking with cognitive decay modeling in a local on-device database.
    15
    MIT

  • rekal

    janbjorge
    A
    license
    Not graded
    quality
    A
    maintenance
    Provides long-term memory for LLMs via local SQLite storage with hybrid search (BM25, vectors, recency decay), enabling AI coding agents to persist and recall memories across sessions without cloud or API keys.
    53
    MIT

  • MCP Vector Memory

    vertexhub-ai
    A
    license
    Not graded
    quality
    Not graded
    maintenance
    Provides AI coding agents with persistent, long-term memory through local semantic search and SQLite storage. It enables agents to save and retrieve architectural decisions or project context across different conversation sessions without requiring cloud services.
    MIT

  • hive-memory

    moonx010
    A
    license
    Not graded
    quality
    C
    maintenance
    Provides AI coding agents with persistent, graph-connected memory across projects, enabling cross-project context retrieval via synaptic connections and hybrid search.
    6 npm
    8
    MIT

  • memento

    UmoLab
    A
    license
    Not graded
    quality
    A
    maintenance
    Provides persistent memory for AI coding agents via MCP, enabling agents to store and semantically recall facts, events, and lessons across sessions, all running locally without cloud dependencies.
    Apache 2.0
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

A3.8/5.0

Scored across 9 tools

Disambiguation5/5

Each tool maps to a distinct action—searching, fetching by slug, listing, writing, updating, learning, recalling, reinforcing, and pinning. Even the superficially similar mem_search and mem_recall are clearly separated by mem_recall's skill-specific retrieval, strength weighting, and reinforcement side effect.

Naming Consistency5/5

All tools use the mem_ prefix followed by a consistent imperative verb: search, get, list, write, update, learn, recall, reinforce, pin. The naming pattern makes each tool's purpose predictable and the set highly uniform.

Tool Count5/5

Nine tools is well-scoped for a memory and skill management server. The set covers retrieval, record lifecycle, skill learning, reinforcement, and pinning without unnecessary duplication or bloat.

Completeness4/5

The tool surface covers creation, retrieval, update, and the skill feedback loop thoroughly. The main gap is lifecycle cleanup: there is no explicit delete or archive tool, and the untrusted-data approval state mentioned in mem_get has no corresponding approval action.

Maintenance

ActivityMaintained
ResponsivenessUnresponsive

Resources