PQS - Prompt Quality Score
A remote MCP server exposing 3 tools via Model Context Protocol: score_prompt (free, grades any LLM prompt A-F on 0-40 scale), optimize_prompt (returns optimized prompt + dimension breakdown, $0.025 USDC), and compare_models (Claude vs GPT-4o head-to-head, $1.25 USDC). Remote HTTP server at /api/mcp.
README
PQS MCP Server
The world's first named AI prompt quality score — as an MCP server.
Score, optimize, and compare LLM prompts before they hit any model. Built on PEEM, RAGAS, G-Eval, and MT-Bench frameworks.
Install
Claude Desktop
Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"pqs": {
"command": "npx",
"args": ["pqs-mcp-server"]
}
}
}
Smithery
smithery mcp add onchaintel/pqs
Tools
score_prompt (Free — no API key needed)
Score any prompt before it hits any model. Returns grade A-F, score out of 40, and percentile.
Example output:
{
"pqs_version": "1.0",
"prompt": "analyze this wallet",
"vertical": "crypto",
"score": 8,
"out_of": 40,
"grade": "D",
"upgrade": "Get full dimension breakdown at /api/score for $0.025 USDC via x402",
"powered_by": "PQS — pqs.onchainintel.net"
}
optimize_prompt ($0.025 USDC via x402)
Score AND optimize any prompt. Returns full 8-dimension breakdown + optimized version.
Requires: PQS API key (get one free at pqs.onchainintel.net)
compare_models ($1.25 USDC via x402)
Compare Claude vs GPT-4o on the same prompt. Judged by a third model. Returns winner, scores, and recommendation.
Requires: PQS API key (get one free at pqs.onchainintel.net)
Verticals
Specify the domain context for more accurate scoring:
software— Software engineering, code, debuggingcontent— Content creation, copywriting, social mediabusiness— Business analysis, finance, strategyeducation— Education, research, academic writingscience— Scientific research, data analysiscrypto— Crypto trading, DeFi, onchain analysisgeneral— General purpose (default)
Quality Gate Pattern
Use PQS as a pre-inference quality gate:
const score = await fetch("https://pqs.onchainintel.net/api/score/free", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ prompt: userPrompt, vertical: "software" })
});
const { score: pqsScore } = await score.json();
if (pqsScore < 28) throw new Error("Prompt quality too low — improve and retry");
Grade D or below (< 28/40) means the prompt will waste inference spend.
Built by
John / OnChainIntel — @OnChainAIIntel
pqs.onchainintel.net
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.