io.github.OnChainAIIntel/pqs-mcp-server
NPM · PQS-MCP-SERVER · 2 COMPONENTS · SCANNED SEP 20
PQS scores any prompt before the model runs. 8 dimensions. 5 frameworks. Pre-flight, not post-hoc.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 35 of 101 dependencies flagged as unhealthy (1 deprecated). View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 116 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability69
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 736 tokens (~368/item across 2 items; 2 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management90
- Stability observed for 27 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 2 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 2 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the io.github.OnChainAIIntel/pqs-mcp-server server?
io.github.OnChainAIIntel/pqs-mcp-server runs locally as an npm package, launched with npx -y pqs-mcp-server. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · pqs-mcp-server
claude mcp add onchainaiintel-pqs-mcp-server -- npx -y pqs-mcp-server
{
"mcpServers": {
"onchainaiintel-pqs-mcp-server": {
"command": "npx",
"args": [
"-y",
"pqs-mcp-server"
]
}
}
} {
"servers": {
"onchainaiintel-pqs-mcp-server": {
"command": "npx",
"args": [
"-y",
"pqs-mcp-server"
]
}
}
} codex mcp add onchainaiintel-pqs-mcp-server -- npx -y pqs-mcp-server
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"onchainaiintel-pqs-mcp-server": {
"type": "local",
"command": [
"npx",
"-y",
"pqs-mcp-server"
],
"enabled": true
}
}
} openclaw mcp add onchainaiintel-pqs-mcp-server --command npx --arg -y --arg pqs-mcp-server
mcp_servers:
onchainaiintel-pqs-mcp-server:
command: "npx"
args: ["-y", "pqs-mcp-server"] {
"McpServers": {
"onchainaiintel-pqs-mcp-server": {
"Transport": "stdio",
"Command": "npx",
"Arguments": [
"-y",
"pqs-mcp-server"
]
}
}
} assistant mcp add onchainaiintel-pqs-mcp-server -t stdio -c npx -a -y pqs-mcp-server
{
"mcpServers": {
"onchainaiintel-pqs-mcp-server": {
"command": "npx",
"args": [
"-y",
"pqs-mcp-server"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 19 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.
- 17 Sept 26 −3
- Stability: pass → 0.80 functional
- 16 Sept 26 +1
- Stability: 0.97 → pass security
- 14 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.
- 12 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.
- 10 Sept 26 −3
- Stability: pass → 0.80 functional
- 9 Sept 26 +1
- Stability: 0.97 → pass security
- 7 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 20 Sept 2026 · Analysed npm/pqs-mcp-server@1.4.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Dependencies 101 packages
| Packages resolved | 101 |
|---|---|
| Deprecated | 1 |
| Stale | 34 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
optimize_prompt ~426
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.
| Name | Type | Req | Description |
|---|---|---|---|
| api_key | string | – | PQS API key from a Pro subscription. Required. Format: pqs_live_… (32+ characters). Subscribe at https://promptqualityscore.com/pricing?utm_source=mcp&utm_medium=schema_description_v140&utm_campaign=… |
| prompt | string | yes | The prompt to optimize. Max 8000 characters. |
No output schema declared.
No examples provided.
score_prompt ~310
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.
| Name | Type | Req | Description |
|---|---|---|---|
| prompt | string | yes | The prompt text to score. Single prompt, not a conversation. Max 8000 characters. |
No output schema declared.
No examples provided.
What is the io.github.OnChainAIIntel/pqs-mcp-server server?
io.github.OnChainAIIntel/pqs-mcp-server is listed in the public MCP registry as io.github.OnChainAIIntel/pqs-mcp-server. PQS scores any prompt before the model runs. 8 dimensions. 5 frameworks. Pre-flight, not post-hoc. This page covers its npm package (pqs-mcp-server).
Is the io.github.OnChainAIIntel/pqs-mcp-server server safe to use?
io.github.OnChainAIIntel/pqs-mcp-server scores 81 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.OnChainAIIntel/pqs-mcp-server server expose?
io.github.OnChainAIIntel/pqs-mcp-server exposes 2 tools: score_prompt, optimize_prompt. Their descriptions and schemas cost roughly 736 tokens of context every time the server is loaded.
Is the io.github.OnChainAIIntel/pqs-mcp-server server still maintained?
io.github.OnChainAIIntel/pqs-mcp-server is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the io.github.OnChainAIIntel/pqs-mcp-server server under?
io.github.OnChainAIIntel/pqs-mcp-server declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.