Skip to main content
Glama

Related Servers

Alternatives to Agent Memory Engine

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Provides durable project context for coding agents, including project maps, session history, and explicit memories, all stored locally.
      10 npm
      7
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Provides persistent project memory for AI coding agents, enabling context retention across sessions via event logging, briefing generation, and querying.
      MIT
    • 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.
      8 npm
      8
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides AI coding assistants with persistent project memory to retain architectural decisions, code patterns, and domain knowledge across sessions. It stores data locally in a SQLite database, allowing agents to remember, recall, and manage project-specific context using full-text search.
      3 npm
      Apache 2.0

    TDQS

    A3.7/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a distinct purpose: inspecting knowledge vs. memory vs. status vs. reflection vs. refresh vs. context retrieval. The descriptions clearly differentiate them, so an agent can easily select the appropriate tool.

    Naming Consistency4/5

    Five tools follow a verb_noun pattern (e.g., inspect_knowledge, retrieve_agent_context), but memory_status uses a noun_noun format, which is a minor deviation. Overall, naming is mostly consistent and readable.

    Tool Count5/5

    Six tools is well-scoped for an agent memory engine, covering the essential operations: inspection, status, reflection, refresh, and context retrieval. The count is neither too few nor excessive.

    Completeness4/5

    The tool set covers core workflows: reading memory/knowledge, monitoring status, triggering reflection, and refreshing knowledge. However, it lacks explicit tools for direct memory creation or deletion, relying on the reflection pipeline for writing, which may be a minor gap.

    Maintenance

    ActivitySlowing
    ResponsivenessUnresponsive