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Alternatives to openmem-mcp

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  • A
    license
    Not graded
    quality
    A
    maintenance
    Provides AI coding agents with a persistent memory layer to save, recall, update, and track memories across sessions and repositories using hybrid semantic search.
    6
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Provides persistent, local-first memory for coding agents with Markdown as the source of truth, exposed via CLI, loopback API, MCP, and Codex hooks for context retrieval and durable writes.
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.
    5
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Shareable memory for AI coding agents. Enables agents to remember and recall durable memories across sessions and share them as importable packs.
    1 npm
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Provides persistent memory for AI coding agents, enabling them to save, search (hybrid vector/BM25/concept graph), list sessions, and forget memories via MCP tools.
    11 npm
    Apache 2.0
  • F
    license
    Not graded
    quality
    A
    maintenance
    Provides a local-first persistent memory layer that lets AI coding agents store, recall, and semantically search project-specific and cross-project knowledge across sessions, so context, decisions, and guidelines survive between conversations. Runs entirely on the user's machine with SQLite and no API keys, and optionally supports autonomous task-queue execution built on the same memory.
    -

TDQS

B3.2/5.0

Scored across 10 tools

Disambiguation4/5

Most tools have distinct operations, but memory_recall, memory_search, and memory_reflect overlap in retrieval/synthesis semantics. The descriptions clarify provider-specific behavior, which mostly resolves the ambiguity.

Naming Consistency5/5

All tools use a consistent snake_case memory_* prefix and clear verb/noun patterns. The naming is predictable across the entire set.

Tool Count5/5

Ten tools is well-scoped for a memory-provider abstraction layer. Each tool covers a meaningful operation such as add, search, export, status, consolidation, or scoping.

Completeness4/5

The surface covers creation, retrieval, deletion, import/export, provider status, synthesis, consolidation, and project scoping. Minor gaps exist around direct update or get-by-id operations, but core workflows are covered.

Maintenance

ActivityMaintained
ResponsivenessNo issues