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Related Servers

Alternatives to coding-os

No user-submitted related servers found.

    Related Servers

    • 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
      A
      quality
      B
      maintenance
      MCP server for orchestrating coding tasks with frontier-model planning and local execution, enabling manifest validation, plan submission, status checks, cancellation, and report retrieval through Claude Code.
      6
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      MCP server that exposes local agents as tools for Claude Code, enabling capabilities in quant, trading, news, reports, robotics, Notion, and FreeCAD.
      33 npm
      1
      -

    TDQS

    B3/5.0

    Scored across 89 tools

    Disambiguation2/5

    Several tool clusters have overlapping purposes: cos_graph_query vs cos_graph_search vs cos_graph_resolve, cos_search vs cos_doc_search vs cos_task_search, cos_task_pick vs cos_task_claim_next, and cos_supervise vs cos_dispatch_formula. Descriptions attempt to differentiate boundaries, but with 89 tools an agent must read carefully to avoid misselection.

    Naming Consistency4/5

    All tools consistently use the cos_ prefix and snake_case, which makes the set predictable at the casing level. However, the underlying convention mixes verb_noun (cos_task_create) with noun phrases (cos_graph_contracts, cos_task_by_filter, cos_health), so it is not a perfectly uniform pattern.

    Tool Count1/5

    89 tools is far beyond the recommended 3-15 range and represents an extreme mismatch for a single server. The surface is fragmented across graph analysis, task management, memory, retrieval, metrics, and supervision, making discovery and selection costly.

    Completeness4/5

    The server covers task lifecycle, graph exploration, memory learning, retrieval quality, metrics, and supervision with extensive operations. Minor gaps exist, such as explicit documentation authoring or task deletion, but core workflows for the stated coding-OS domain are largely complete.

    Maintenance

    ActivityMaintained
    ResponsivenessWithin a week