Skip to main content
Glama
fantasieleven-code

callout-dev

by fantasieleven-code
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Related Servers

Alternatives to callout-dev

No user-submitted related servers found.

    Related Servers

    • second-opinion-mcp

      mauricioreiss
      A
      license
      Not graded
      quality
      D
      maintenance
      MCP server that gives any AI coding tool a structured second opinion from another AI provider.
      4 npm
      MIT

    • greybeard

      btotharye
      A
      license
      Not graded
      quality
      C
      maintenance
      An MCP server that provides AI-powered code review and architecture analysis, simulating the perspective of an experienced staff engineer. It integrates with IDEs to review diffs, design decisions, and tradeoffs through natural language.
      1
      MIT

    • dev-skills

      parikrut
      A
      license
      Not graded
      quality
      C
      maintenance
      An MCP server that equips AI assistants with specialized, opinionated development playbooks for building microservices, frontends, databases, and DevOps pipelines. It integrates with clients like VS Code Copilot, Claude Desktop, and Cursor to provide battle-tested expertise.
      74 npm
      MIT
    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

    A3.7/5.0

    Scored across 16 tools

    Disambiguation4/5

    Most tools have distinct purposes, but there is some overlap between 'coach' and 'review' that could cause confusion, as both analyze aspects of the project. However, their descriptions clarify that 'coach' focuses on developer behavior patterns while 'review' focuses on architecture and expert perspectives, which helps mitigate misselection.

    Naming Consistency5/5

    Tool names follow a consistent snake_case pattern with clear verb_noun structures, such as 'todo_add', 'todo_list', 'save_review_findings', and 'set_target_user'. This predictability makes the tool set easy to navigate and understand.

    Tool Count5/5

    With 16 tools, the server is well-scoped for its purpose of project management and AI collaboration support. Each tool serves a specific function, such as idea scoring, reviews, recommendations, and todo management, without feeling excessive or lacking in coverage.

    Completeness5/5

    The tool set provides comprehensive coverage for the domain, including project initialization, idea evaluation, multi-perspective reviews, recommendation management, and todo tracking. There are no obvious gaps; tools like 'recommend_dismiss' and 'recommend_reset' add nuance, ensuring agents can handle full workflows without dead ends.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources