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    Related Servers

    • A
      license
      Not graded
      quality
      F
      maintenance
      Living typed knowledge graph for software projects, exposed over MCP so coding assistants can capture and query modules, capabilities, flows, events, rules and decisions across sessions. SQLite-backed, schema-validated, ships as a Claude Code plugin.
      MIT
    • A
      license
      B
      quality
      A
      maintenance
      MCP server for coding-os, a cognitive operating system that gives AI agents memory, structure, and discipline. It exposes tools for project management, task tracking, knowledge graphs, and cognition traces to Claude Code and Codex.
      89
      41 PyPI
      7
      Apache 2.0
    • A
      license
      Not graded
      quality
      D
      maintenance
      A local knowledge graph server that captures and provides access to a project's decision history, enabling AI agents to navigate past decisions, dead-ends, and constraints via MCP tools.
      2
      AGPL 3.0
    • A
      license
      Not graded
      quality
      A
      maintenance
      This MCP server exposes a local structural code graph and project memory so AI coding agents can retrieve focused code entities, relationships, and prior mistakes before reading full files. It enables bounded context queries, caller/callee and impact analysis, and carryover of recorded session information through a CLI, hooks, and an authenticated local dashboard.
      24 npm
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      A local MCP server that provides a shared context and learning foundation across multiple AI tools (Claude, Copilot, Codex) for multiple projects, enabling persistent knowledge, decisions, and gap reflection through note storage.
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    • A
      license
      A
      quality
      B
      maintenance
      Code intelligence MCP server for Claude Code providing multi-project code graph, semantic search, session history, knowledge base, and web search.
      15
      4
      MIT

    TDQS

    B3.1/5.0

    Scored across 25 tools

    Disambiguation4/5

    Most tools target distinct resources/actions, and descriptions explicitly differentiate the potentially overlapping ones (create_edge vs atomic create_edges, search_nodes vs find_similar vs briefing). The search/discovery cluster (search_nodes, find_similar, briefing, overview) and get_node(neighbor_depth) vs get_subgraph/neighbors carry mild overlap, but guidance mitigates it.

    Naming Consistency4/5

    Core mutators follow a clean verb_noun pattern (create_node, update_node, delete_node, rename_node, merge_nodes, create_edge, delete_edge). Read-only analytics/report tools use bare-noun forms (orphans, stale, contradictions, overview, briefing), which is a consistent secondary convention rather than random mixing.

    Tool Count3/5

    25 tools sits at the heavy end of the acceptable band. Each is distinct, but the seven separate audit queries (decisions_without_rationale, open_questions, orphans, contradictions, stale, dangling_edges, case_collisions) suggest the surface could be consolidated somewhat.

    Completeness4/5

    Full node lifecycle (create/get/update/rename/merge/delete), edge create-batch/delete, search/dedup, maintenance (reindex/snapshot), and rich reporting/audit coverage are all present. Only minor gaps (no in-place edge update, though delete+recreate covers it) leave it just shy of complete.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues