Skip to main content
Glama
tinhien11

remem-mcp

by tinhien11
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Related Servers

Alternatives to remem-mcp

No user-submitted related servers found.

    Related Servers

    • memnant

      peureka
      A
      license
      Not graded
      quality
      A
      maintenance
      Persistent memory MCP server that remembers decisions and context across coding sessions, automatically logging and surfacing relevant knowledge as you work.
      82 npm
      MIT

    • knitbrain

      PDgit12
      A
      license
      A
      quality
      A
      maintenance
      Local-first MCP server that gives any AI coding agent per-project memory, workflow intelligence, and always-on, lossless token & context optimization.
      37
      60 npm
      6
      MIT

    • MemoSaver

      akufikri
      A
      license
      Not graded
      quality
      B
      maintenance
      Local-first MCP server that persists AI coding agent memory and session context, enabling seamless resume across sessions with searchable memories and checkpoints.
      4 npm
      1
      MIT

    • kontexta

      safiyu
      A
      license
      A
      quality
      A
      maintenance
      A local-first MCP server that gives AI coding agents persistent memory and controlled commands. Features a git-backed markdown knowledge vault with FTS5 search, surgical section edits, token-aware context budgeting, and a sandboxed command engine with human approval gates. Works with Claude Code, Cursor, Copilot, Gemini, and more.
      4
      58
      249 npm
      1
      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

    A3.6/5.0

    Scored across 48 tools

    Disambiguation4/5

    Most tools target distinct actions and resources, but the large number of memory-management tools (confirm, correct, supersede, resolve, feedback, record_outcome, consolidate) have overlapping conceptual boundaries that could cause an agent to pick the wrong one. The recall/search/related trio is also somewhat redundant, though each has a clear retrieval purpose.

    Naming Consistency3/5

    Naming uses a rough prefix-based pattern for knowledge, codegraph, wiki, and skill tools, but mixes bare verbs (capture, recall, forget, resolve) with noun_verb pairs (knowledge_get, skill_list) and stacked prefixes (codegraph_detect_changes). The convention is readable but not consistent across the toolset.

    Tool Count2/5

    48 tools is a very large surface for a single MCP server. While the breadth covers multiple domains (memory, knowledge, codegraph, wiki, skills, sessions, corrections), the sheer count makes the set unwieldy and likely to overwhelm agents when selecting the right tool.

    Completeness5/5

    The tool surface is remarkably comprehensive: full CRUD for memories and knowledge assets, multiple retrieval modes, graph traversal, impact analysis, wiki ingestion, skill lifecycle, session management, correction tracking, and diagnostics. Obvious gaps are minor (e.g., no skill_update, no wiki_delete), but agents can complete virtually any workflow in the stated domain.

    Maintenance

    ActivityActive
    ResponsivenessResponsive

    Resources