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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
    52 npm
    6
    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.
    56 npm
    92
    -
  • 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
    486
    MIT
  • A
    license
    A
    quality
    B
    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

A3.9/5.0

Scored across 30 tools

Disambiguation4/5

The families (memory_*, notes_*, tasks_*, gardener_*, session_*, project_*) each cover a distinct resource, and descriptions explicitly explain when to use write vs append vs edit and create vs update vs append. The main residual risk is memory_write's in-place update overlapping with memory_edit/memory_append, but the prose carefully steers each case. Overall, tools are largely distinguishable.

Naming Consistency4/5

Names are uniformly snake_case and grouped under predictable prefixes (memory_, notes_, tasks_, gardener_, session_, project_), giving a clear verb_noun pattern within each family. A few outliers (recall, usage_summary, capture_url, favorite_set) break the pattern but are readable and few. Minor deviations only.

Tool Count3/5

30 tools is on the heavy side for a knowledge/memory server, with fine-grained splits like memory_write/append/edit and notes_create/append/edit/update that could be consolidated. The breadth (memory, notes, tasks, sessions, projects, gardener) partly justifies the count, but it sits in the borderline-heavy range. Each tool does earn a role, so it is not chaotic.

Completeness4/5

Coverage across memory, notes, tasks, sessions, and gardener is thorough, including lifecycle (create/read/edit/append/delete), retrieval (recall), and metadata (favorite_set, tags). Gaps are minor: no project update/delete/rename and no dedicated note listing, though recall and remaining tools largely compensate. Core workflows have no dead ends.

Maintenance

ActivityActive
ResponsivenessNo issues