Pqs MCP Server
io.github.OnChainAIIntel/pqs-mcp-server
not responding
Pqs MCP Server is listed as active in the registry but did not answer our last check. 72 installs a week from npm. It exposes 2 tools. Last commit 27 May 2026.
PQS scores any prompt before the model runs. 8 dimensions. 5 frameworks. Pre-flight, not post-hoc.
Installs per day
peak 34 · avg 12 · -23% w/w
a month agotoday
Uptime history
39 hours of history · worst hour 0%
39 hours agonow
13.0%
Uptime 24h
12 of 92 checks
2
Tools
read from the server
838 ms
Response time
average over 24h
72
Installs / week
npm and PyPI
Connect this server
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 2 min ago.
run in your terminal
claude mcp add pqs-mcp-server --transport http https://promptqualityscore.com/api/mcp~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"pqs-mcp-server": {
"url": "https://promptqualityscore.com/api/mcp"
}
}
}~/.codex/config.toml
[mcp_servers.pqs-mcp-server]
url = "https://promptqualityscore.com/api/mcp".cursor/mcp.json
{
"mcpServers": {
"pqs-mcp-server": {
"url": "https://promptqualityscore.com/api/mcp"
}
}
}.vscode/mcp.json
{
"mcpServers": {
"pqs-mcp-server": {
"url": "https://promptqualityscore.com/api/mcp"
}
}
}Available tools 2
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
optimize
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.
score
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.
Endpoints
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://promptqualityscore.com/api/mcp | streamable-http | answering | 86 ms | 2 min ago |
Pqs MCP Server — questions
Answers built from our own checks of this server.
What can Pqs MCP Server do?
It exposes 2 tools, read directly from the server on our last check. Among them: optimize_prompt, score_prompt. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README.
How MCP servers expose tools in the first place →
Is Pqs MCP Server working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 12 of 92 checks got a reply (13.0%), average response time 838 ms. The bar chart above shows every period we have measured.
The registry lists Pqs MCP Server as active — why does it not respond?
The official MCP registry stores what the author submitted; it does not verify that the server still runs. We check the endpoint ourselves, and this one does not answer. Catalogues that copy the registry without checking will show it as working.
How do I connect Pqs MCP Server?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Pqs MCP Server need an API key?
No. Pqs MCP Server completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 2 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Pqs MCP Server?
It answers our handshake in 838 ms on average, which is faster than 9% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.
How many people use Pqs MCP Server?
The npm package pqs-mcp-server was installed 72 times in the last week. Week over week that is -23%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is Pqs MCP Server open source?
Yes — it is published under the MIT licence, written in JavaScript and 2 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.