Pqs Mcp Server

io.github.OnChainAIIntelPublished by GitHub account OnChainAIIntelv1.4.0Updated Nov 2, 2026

PQS scores any prompt before the model runs. 8 dimensions. 5 frameworks. Pre-flight, not post-hoc.

VerifiedStreamable HTTPWeb executableDeveloper ToolsAI & ML

Overview

AI-generated overview

Scores and rewrites LLM prompts against the PQS rubric, giving an assistant a pre-flight quality check before sending prompts to a model.

What you can do
  • Score a prompt across 8 dimensions, returning a 0-80 total, an A-F grade and the weakest dimension
  • Rewrite a prompt to score higher and compare before/after scores with side-by-side sample outputs from a frontier model
  • Receive structured suggestions and error payloads that point to the paid upgrade path
When to use it
Useful when you want to check or improve prompt quality before spending inference on an expensive model, or when building a pre-inference quality gate. The free scoring tool is enough for occasional checks; the rewrite tool is only worth it with a Pro subscription.
Requirements
Runs as a remote streamable-HTTP endpoint or as a local npm package via npx (Node.js). The optimize_prompt tool needs a PQS Pro API key supplied as the PQS_API_KEY environment variable or an api_key argument; score_prompt needs no key. Network access to the PQS service is required, and PQS_BASE can override the backend URL.
Before you install
optimize_prompt requires a paid Pro subscription (about $19.99/month) and sends prompt text to the PQS service and a frontier model for comparison. Free scoring is rate-limited per IP (5/min, 10/day, 100/month). Low scores return promotional suggestion text with subscribe links that the assistant may relay to the user.

Installation

In SourceWeft

  1. Open Pqs Mcp Server in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.OnChainAIIntel%2Fpqs-mcp-server/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "pqs": {
      "type": "http",
      "url": "https://promptqualityscore.com/api/mcp"
    }
  }
}

README

[smithery badge] [GitHub Marketplace] [pqs-mcp-server MCP server]

PQS 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.

Install

Claude Desktop (stdio)

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json):

json
{  "mcpServers": {    "pqs": {      "command": "npx",      "args": ["-y", "pqs-mcp-server"]    }  }}

Remote (HTTP)

Use this when your MCP client supports streamable-HTTP transport (no local npm install required):

json
{  "mcpServers": {    "pqs": {      "url": "https://promptqualityscore.com/api/mcp"    }  }}

Smithery

bash
smithery mcp add onchaintel/pqs

Tools

score_prompt (Free, no API key required)

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):

json
{  "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.

optimize_prompt (Pro subscription required)

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 sent
  • api_key_invalid: key not recognized
  • subscription_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 issue
  • service_unavailable: upstream 5xx

Quality Gate Pattern

Use PQS as a pre-inference quality gate:

javascript
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.

x402 (legacy pay-per-call)

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.

Self-hosting

Override the PQS backend URL with the PQS_BASE environment variable:

bash
PQS_BASE=https://your-pqs-host.example.com npx pqs-mcp-server

Defaults to https://promptqualityscore.com.

Built by

OnChainIntel, @OnChainAIIntel promptqualityscore.com

Source: README.md at commit 70914c0

Tools

2

score_prompt

Score a prompt's quality across 8 dimensions BEFORE sending it to an expensive model. Returns a 0-80 score, an A-F grade, the per-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. USE WHEN: - The user is workshopping a prompt and asks "is this good?" / "will this work?" / "should I add more detail?" - The user is about to send a long or expensive prompt to GPT-4, Claude Opus, or any frontier model, especially in a batch or automation context where rework is costly. - The user mentions iterating on a prompt that produced poor output and wants to diagnose what's missing. - The user pastes a prompt and asks for feedback on it. DO NOT USE WHEN: - The user is asking you to write a prompt for them (write it yourself first, then optionally call score_prompt to verify). - The prompt is conversational chat (this scores task-shaped prompts). COST: Free, no API key required. Rate-limited per IP: 5/min, 10/day, 100/month. If the user exceeds the limit, the response will include a structured upgrade path with subscribe and account URLs. LATENCY: ~2 seconds.

Parameterspromptrequired

optimize_prompt

Rewrite a prompt to score higher on the PQS rubric, AND show before/after output comparisons so the user can see the impact. Returns the optimized prompt, the original PQS score, the optimized PQS score, and side-by-side sample outputs from a frontier model using both versions. USE WHEN: - The user got a low score from score_prompt and asks how to improve. - The user explicitly asks to "improve" / "rewrite" / "fix" / "optimize" a prompt they pasted. - The user is dissatisfied with output quality from a previous prompt and asks how to get better results. - score_prompt returned a suggestion to invoke this tool. DO NOT USE WHEN: - The user just asked for a score (use score_prompt only — don't double up). - The user wants you to write a new prompt from scratch (write it directly). REQUIRES: A PQS API key from a Pro subscription ($19.99/month, 1,000 calls/mo, includes batch + A/B comparison). If the user has not provided one, the tool returns a clear subscription URL — pass that response to the user verbatim. Do not invent or guess API keys. There is no free trial of this tool; the user must subscribe before the first call. COST: Counted against your Pro subscription's monthly call quota. LATENCY: ~6-8 seconds.

Parameterspromptrequiredapi_key

Version history

1
  1. v1.4.0LatestSep 16, 2026

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