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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 optimize
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.
smithery badge GitHub Marketplace pqs-mcp-server MCP server
Score prompt quality before it reaches any AI model. An MCP server for PQS.
Score and optimize LLM prompts before they hit any model. Built on PEEM, RAGAS, MT-Bench, G-Eval, and ROUGE.
Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"pqs": {
"command": "npx",
"args": ["-y", "pqs-mcp-server"]
}
}
}
Use this when your MCP client supports streamable-HTTP transport (no local npm install required):
{
"mcpServers": {
"pqs": {
"url": "https://promptqualityscore.com/api/mcp"
}
}
}
smithery mcp add onchaintel/pqs
Returns a 0-80 score, A-F grade, full 8-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. Rate-limited per IP: 5/min, 10/day, 100/month.
Low- and mid-band scores also include a structured suggestion field with a message, a next_tool pointer to optimize_prompt, and a subscribe URL the consuming LLM can paraphrase back to the user.
Example output (low-band score, suggestion attached):
{
"pqs_version": "2.0",
"prompt": "analyze this wallet",
"score": 9,
"out_of": 80,
"grade": "F",
"dimensions": {
"clarity": 2,
"specificity": 1,
"context": 1,
"constraints": 1,
"output_format": 1,
"role_definition": 1,
"examples": 1,
"cot_structure": 1
},
"weakest_dimension": "specificity",
"powered_by": "PQS — promptqualityscore.com",
"suggestion": {
"message": "This prompt scored 9/80 (F) — significant room to improve. The optimize_prompt tool rewrites it and shows side-by-side outputs from a frontier model, so you can see the impact. optimize_prompt is part of PQS Pro ($19.99/mo, 1,000 calls/mo). Subscribe at https://promptqualityscore.com/pricing?utm_source=mcp&utm_medium=suggestion_v140&utm_campaign=2026-05-mcp-tools-v140.",
"next_tool": "optimize_prompt",
"subscribe_url": "https://promptqualityscore.com/pricing?utm_source=mcp&utm_medium=suggestion_v140&utm_campaign=2026-05-mcp-tools-v140"
}
}
If the per-IP rate limit is hit, the response is a structured rate_limit_exceeded payload with subscribe and account URLs.
Rewrites a prompt to score higher and runs both versions through a frontier model so the user can see the before/after output. Returns the optimized prompt, before/after dimension scores (with totals), improvement_pct, and side-by-side sample outputs.
Pro subscription required ($19.99/mo, 1,000 calls/mo, includes batch + A/B comparison). Subscribe at promptqualityscore.com/pricing.
If the API key is missing, invalid, or on the Free tier, the tool returns a structured error pointing the user at the right URL. No silent failures, no inventing keys. Errors emitted:
api_key_required: no api_key argument was sentapi_key_invalid: key not recognizedsubscription_required: key is valid but Free tier (subscribe to upgrade)rate_limited: per-minute burst limit reached (Pro is rate-limited per minute, not per month) or temporary upstream capacity issueservice_unavailable: upstream 5xxUse PQS as a pre-inference quality gate:
const score = await fetch("https://promptqualityscore.com/api/score/free", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ prompt: userPrompt })
});
const { score: pqsScore } = await score.json();
if (pqsScore < 56) throw new Error("Prompt quality too low. Improve and retry.");
Grade D or below (under 56/80) means the prompt will waste inference spend.
The MCP tools in this package use the SaaS API-key model. A separate x402-native pay-per-call path is available via the canonical PQS HTTP API (no API key, caller settles USDC on Base on-chain). For x402 integration, see the canonical pricing and discovery artifacts at promptqualityscore.com.
Override the PQS backend URL with the PQS_BASE environment variable:
PQS_BASE=https://your-pqs-host.example.com npx pqs-mcp-server
Defaults to https://promptqualityscore.com.
OnChainIntel, @OnChainAIIntel promptqualityscore.com
Выполни в терминале:
claude mcp add pqs-prompt-quality-score -- npx CSA PROJECT - FZCO © 2026 IFZA Business Park, DDP, Premises Number 31174 - 001
Безопасность
Низкий рискАвтоматическая эвристика по публичным данным — не гарантия безопасности.