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Related Servers

Alternatives to Seamless

  • A
    license
    A
    quality
    A
    maintenance
    MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.
    4
    72 npm
    4
    MIT

Related Servers

  • F
    license
    Not graded
    quality
    D
    maintenance
    Shared memory and orchestration for coding agents, enabling persistent knowledge, multi-agent coordination, and a canonical workflow across MCP-compatible AI clients.
    34 npm
    110
    -
  • A
    license
    Not graded
    quality
    A
    maintenance
    Local-first, file-based memory layer for AI agents — one shared Markdown vault across Claude, Codex, Gemini, Cursor and any MCP client. Provides read/write memory tools with an audit trail, per-agent trust levels, and Git sync; no cloud and no lock-in.
    2
    MIT
  • A
    license
    B
    quality
    D
    maintenance
    A shared memory layer for AI agents — one memory.md synced across Claude Desktop, Cursor, Claude Code, OpenAI Codex, and any MCP client.
    4
    2
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Persistent memory for AI agents as a single Go binary: hybrid recall, self-building knowledge graph, and a live TUI dashboard. Zero infra, offline-first — works with Claude Code, Cursor, Codex, OpenCode, and any MCP client.
    5
    480
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Local MCP server giving AI coding agents (Claude Code, Cursor, VS Code/JetBrains Copilot) a shared, persistent memory of your projects and every bug/issue faced during development. Stateless, plain-file storage (AGENTS.md + issues.jsonl) — no database.
    16
    54 npm
    1
    MIT
  • A
    license
    B
    quality
    D
    maintenance
    Local Markdown-backed memory tools for Codex and other MCP-capable agents. Exposes durable agent knowledge via CLI and MCP server.
    5
    MIT

TDQS

A4/5.0

Scored across 30 tools

Disambiguation4/5

Most tools are cleanly separated by resource prefix (memory_, notes_, tasks_, project_, session_, gardener_) and the descriptions clearly state when to prefer each one. The main ambiguity risk is the write/edit/append cluster within memories and notes, where the boundaries are subtle despite thorough descriptions.

Naming Consistency4/5

The dominant <resource>_<action> pattern (memory_write, notes_read, tasks_claim, project_list, session_start) makes the set predictable. A few outliers break it: capture_url and recall use verb-first forms, usage_summary is a noun phrase, and favorite_set inverts the usual action-object ordering.

Tool Count2/5

30 tools is well past the 25+ threshold and the set feels inflated by parallel exact-search/replace, whole-body-update, and append variants for both memories and notes, plus multiple gardener planning entry points. The broad domain explains some of the count, but an agent has to navigate a lot of near-synonyms.

Completeness3/5

Memory, note, and task lifecycles are essentially complete, and recall/capture/favorite cover retrieval and intake. Projects are only create/list with no update, rename, or delete path, and sessions have start/update/end but no way to inspect a past session beyond aggregate usage_summary.

Maintenance

ActivityActive
ResponsivenessNo issues