PQS - Prompt Quality Score
OfficialRelated Servers
Alternatives to PQS - Prompt Quality Score
No user-submitted related servers found.
Related Servers
- AlicenseBqualityDmaintenanceAn MCP server providing 22 pay-per-call utility tools for AI agents (scrape, validate, embed, store, moderate, notify, convert, prevent loops) without accounts or API keys, using USDC payments via the x402 protocol.1755 npm1MIT
- AlicenseCqualityDmaintenanceA Model Context Protocol server exposing 58 online tools (crypto, data, image, text, etc.) and workflow execution, enabling MCP clients like Claude Desktop to invoke them via natural language.584 npmMIT
- AlicenseAqualityDmaintenanceAn MCP server for deterministic prompt optimization in Claude Code. Score prompts across 7 quality dimensions, auto-select from 11 Anthropic techniques, and return a structural scaffold.17 npm2MIT

Parlayofficial
AlicenseNot gradedqualityDmaintenanceRemote MCP server for prediction markets — search and compare live odds across Polymarket, Kalshi, and Limitless from Claude, ChatGPT, or Gemini. Six read-only tools, free tier available.6MIT- AlicenseBqualityDmaintenanceDynamic MCP server — 30+ tools across fact verification, agent memory, Indian NLP, contract risk, security threat modelling, sales call intelligence and more. x402/USDC micropayments on Base.336 npmMIT
- FlicenseNot gradedqualityBmaintenanceMCP server for professional prompt engineering and agentic scaffolding, with cloud and local optimization.6-
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one scores a prompt, the other optimizes it. Their use cases and prerequisites are well-defined, so an agent cannot confuse them.
Both tool names follow a consistent verb_noun pattern: 'score_prompt' and 'optimize_prompt'. The naming is uniform and predictable.
With only two tools, the set is narrowly scoped to prompt scoring and optimization. While this is appropriate for the domain, slightly more tools (e.g., subscription management or rubric access) could enhance completeness without bloat.
The server covers the core workflow of scoring and optimizing prompts. However, it lacks tools for subscription management, retrieving the rubric, or performing batch operations, which are minor gaps given the stated dependencies and cost structure.