Skip to main content
Glama

Related Servers

Alternatives to SushiMCP

No user-submitted related servers found.

    Related Servers

    • A
      license
      B
      quality
      C
      maintenance
      This is a powerful Model Context Protocol (MCP) server that integrates multiple AI coding agents—Anthropic Claude Code, OpenAI Codex, and Google Gemini—directly into your workflow. It enables seamless cross-provider analysis, leveraging Gemini's massive token window, Codex's specialized coding capabilities, and Claude's advanced reasoning.
      10
      2 npm
      MIT
    • A
      license
      A
      quality
      D
      maintenance
      A Model Context Protocol server that provides development standards and best practices context to AI coding assistants, ensuring generated code adheres to team/project conventions.
      3
      20 npm
      1
      MIT
    • A
      license
      A
      quality
      D
      maintenance
      Universal MCP server that analyzes any codebase and provides structured context to AI assistants. Dynamic, accurate, and token-efficient.
      18
      7 npm
      MIT

    TDQS

    A3.5/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: fetch_llms_txt and fetch_openapi_spec retrieve content from URLs, while list_llms_txt_sources and list_openapi_spec_sources list available sources for those URLs. There is no overlap in functionality, and the descriptions clearly differentiate between fetching and listing operations for two distinct resource types (llms.txt and OpenAPI specs).

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case: fetch_llms_txt, fetch_openapi_spec, list_llms_txt_sources, and list_openapi_spec_sources. The naming is predictable and readable, with 'fetch' for retrieval actions and 'list' for source enumeration, maintaining uniformity throughout the set.

    Tool Count4/5

    With 4 tools, the count is reasonable for a server focused on fetching and listing documentation sources. It covers two resource types (llms.txt and OpenAPI specs) with complementary operations, but it might feel slightly thin if expanded to handle more documentation formats or additional actions like validation or processing. Overall, it's well-scoped for its apparent purpose.

    Completeness3/5

    The tool set provides basic fetch and list operations for llms.txt and OpenAPI specs, covering retrieval and source discovery. However, there are notable gaps: no tools for updating, deleting, or validating these resources, and no operations for other documentation formats mentioned in descriptions (e.g., llms-full.txt or llms-mini.txt). This limits the surface to read-only actions, which may cause agents to hit dead ends in more complex workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues