Skip to main content
Glama

Related Servers

Alternatives to vibe-prompt-mcp

No user-submitted related servers found.

    Related Servers

    • F
      license
      A
      quality
      C
      maintenance
      Refines and improves AI prompts using workspace-aware context from your project's tech stack, structure, and dependencies. Includes tools to analyze prompt quality and generate well-structured prompts from raw ideas.
      4
      209 npm
      5
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      Context intelligence for AI coding sessions. 7 MCP tools to score, compare, compress, build, and scan prompts across 9 AI tools. Rule-based, <5ms/prompt, all analysis runs locally.
      46
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Static analysis for vibe-coded apps. Flags security, reliability, performance, and AI quality issues in code generated by Cursor, v0, Bolt, and Copilot.
      575 npm
      15
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.
      10
      2 npm
      8
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      A code ingestion tool that transforms your code into AI-optimized prompts instantly. Gather the relevant context with code2prompt under the hood. Learn more at code2prompt.dev
      7,653
      MIT

    TDQS

    D1.8/5.0

    Scored across 2 tools

    Disambiguation4/5

    The two tools, score_prompt and optimize_prompt, suggest distinct actions, though the lack of descriptions leaves some room for overlap. An agent could generally tell them apart by verb alone.

    Naming Consistency5/5

    Both tool names follow the same lowercase snake_case verb_noun pattern: score_prompt and optimize_prompt. The naming is fully consistent.

    Tool Count3/5

    With only two tools, the server feels minimal and near the thin end of the acceptable range. It could be sufficient for a narrowly scoped prompt-tuning server, but the purpose is unclear without descriptions.

    Completeness2/5

    The surface covers scoring and optimizing prompts but lacks obvious supporting operations such as generation, comparison, or iteration. The missing descriptions also make it hard to confirm that the intended workflow is fully covered.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues