Stipple — Reference Verification
Fact-check citations: resolve, match, support claims. Arithmetic rechecked. Free to start.
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"openwarrant-verify": {
"url": "https://www.stipple.sh/mcp-verify"
}
}
}Remote endpoints
https://www.stipple.sh/mcp-verifystreamable-httpWhat it can do
Tool inventory
Tools (1)
🟢verify_references(text, url, bytes_b64, filename, deep)
Fact-check a document's REFERENCES and CLAIMS — built for AI-generated reports whose citations must be checked before they're trusted. USE THIS WHEN someone shares a report, article, whitepaper, or deep-research export (or a link to one) and asks: is this accurate / legit? are these citations real? fact-check this. did the AI make this up? Also use it proactively before relying on any AI-written document. Provide the document ONE way: `url` (a public http(s) link to a PDF or web page — fetched server-side, the cheapest call: no need to download or encode anything), `text` (pasted markdown/plain prose), OR `bytes_b64` (a base64 PDF; URLs are read from the PDF's link annotations, so they're exact). Default (fast): provenance (is it a ChatGPT deep-research export?), citation resolution (live / archived / dead, papers matched against arXiv/Crossref to catch 'real ID, wrong paper'), and internal MATH (recompute the doc's own arithmetic). Set `deep=true` to also fetch each cited source and judge whether it SUPPORTS or CONTRADICTS the claim (slower, ~a minute). Returns a trust summary, per-item tables, and a shareable `permalink` to the public fact-check record. HONEST BOUNDARY: this reports verification COVERAGE, not truth — 'supported' means evidence-backed (not necessarily true) and 'unsupported' means no evidence found (not necessarily false). It tells a reviewer WHERE to look; it does not bless the document, and it never affects the fraud risk band.
Input Schema
{
"type": "object",
"properties": {
"text": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Text"
},
"url": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Url"
},
"bytes_b64": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Bytes B64"
},
"filename": {
"default": "document.pdf",
"title": "Filename",
"type": "string"
},
"deep": {
"default": false,
"title": "Deep",
"type": "boolean"
}
},
"title": "verify_referencesArguments"
}Output Schema
{
"type": "object",
"additionalProperties": true,
"title": "verify_referencesDictOutput"
}Community
Evidence