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    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents to maintain persistent, cross-session memory of codebase architecture, naming conventions, and decisions through MCP tools. Eliminates repetitive project re-explanation by automatically injecting stored context into every session with local-first SQLite storage and optional team sharing capabilities.
      4
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents and assistants to share a local-first, token-efficient persistent memory layer across MCP-compatible runtimes, storing typed project facts, decisions, failures, and solutions with temporal validity. It supports offline use and Postgres-compatible storage, so agents can retrieve relevant context without re-embedding entire repositories.
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents to share a persistent local-first memory hub, storing and recalling architectural decisions and context across different tools via MCP, so users can switch assistants without losing context.
      Apache 2.0
    • F
      license
      Not graded
      quality
      A
      maintenance
      Provides local-first, cross-session persistent memory that lets AI coding agents store, semantically search, and recall project-specific and cross-project knowledge via MCP tools and resources, with an optional task queue for autonomous execution.
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents to maintain structured, persistent memory as a typed-edge knowledge graph over contexts, decisions, and tasks, with deterministic auto-threading, trust signals, and replayable story recall. It also exposes a token-lean MCP gateway for on-demand tool discovery, helping agents preserve causal project context across sessions.
      5,295 npm
      5
      MIT

    TDQS

    A3.9/5.0

    Scored across 19 tools

    Disambiguation5/5

    Each tool targets a distinct resource/action, and descriptions explicitly delimit overlapping cases such as full-text search vs. semantic search and update_task vs. complete_tasks. The role/session tools are also clearly differentiated between session start and mid-session role switching.

    Naming Consistency4/5

    Almost all tools use consistent snake_case verb_noun naming, such as list_project_artifacts, save_project_artifacts, and complete_tasks. Minor deviations exist with semantic_search and singular/plural variation between update_task and add_tasks/search_tasks, but the pattern remains highly readable.

    Tool Count4/5

    Nineteen tools is slightly heavy for the typical 3–15 range, but the server spans artifacts, tasks, projects, and sessions, so each tool has a plausible role. The count is reasonable overall, though the surface is broader than a tightly scoped server.

    Completeness3/5

    Artifact lifecycle coverage is strong, including read, save, list, search, move, delete, history, and restore, but the task and project surfaces lack deletion/get-details operations. More importantly, descriptions reference source-browsing tools such as view_file_source, get_project_map, and search_code_skeletons that are absent from the tool set, creating dead ends.

    Maintenance

    ActivityNo data
    ResponsivenessSyncing