MCP server

Stipple — Document Verification & Extraction Official

sh.stipple/openwarrant

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Document forensics: tamper/AI checks, fields, tables, identity, screening, tenders, citations.

Working at last checkVerified publisher: stipple.shAbout 7,874 tokens per request once connected16 tools

Website Source

https://www.stipple.sh/mcp

At a glance

Type: MCP server
Publisher: stipple.sh (verified by the MCP Registry)
Status: Working at last check
Tools: 16
Token cost: About 7,874 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http openwarrant https://www.stipple.sh/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.openwarrant]
url = "https://www.stipple.sh/mcp"

Gemini CLI

{"mcpServers":{"openwarrant":{"httpUrl":"https://www.stipple.sh/mcp"}}}

Cursor

{"mcpServers":{"openwarrant":{"url":"https://www.stipple.sh/mcp"}}}

VS Code

{"servers":{"openwarrant":{"type":"http","url":"https://www.stipple.sh/mcp"}}}

Antigravity

agy mcp add openwarrant https://www.stipple.sh/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"openwarrant","server_url":"https://www.stipple.sh/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"openwarrant","server_url":"https://www.stipple.sh/mcp"}

Tools

buyer_awards ~474 tokens
What a buyer has awarded, what is ending, and what they plan. FREE. USE THIS WHEN someone asks about a specific buyer before a bid: "who holds Transport for NSW's work", "what is ending soon at Queensland Health", "what does this agency usually pay". Give `buyer` (the organisation name as published
check_document ~123 tokens
Cheap cache-check: has this exact document already been inspected? Hash the file yourself (sha256, lowercase hex) and call this before verify_document to skip a redundant (paid) inspection. Returns {cached, warrant_id, permalink}.
check_pack ~534 tokens
Check whether a SET of documents satisfies a checklist — completeness, cheaply. USE THIS WHEN you have an application / onboarding pack and need "do we have the required documents, and what's still missing?" Each document is CLASSIFIED (one cheap page-1 read — never full field extractio
check_source_overlap ~505 tokens
Check whether text OVERLAPS text published on the public web — a plagiarism-style check: does this text appear elsewhere? was this copied? find the source of this text. Provide the document ONE way: `text` (pasted prose), `url` (a public http(s) link — fetched server-side; that page and
detect_ai_text ~442 tokens
Estimate the PROBABILITY that a document's text was AI-GENERATED (LLM-written prose). USE THIS WHEN someone shares prose — an essay, cover letter, article, review, application, or report (or a link to one) — and asks: did an AI / ChatGPT write this? is this human-written? detect AI text
extract_fields ~868 tokens
Extract structured FIELDS from a document (PDF or image) with a vision model. USE THIS WHEN you need specific values OUT of a document — a payslip's gross/net, an invoice's total/ABN, a form's checkboxes, a table's cells — rather than a yes/no about the document. (For "is this genuine?"
find_signals ~519 tokens
Signals: what may be tendered before it is. FREE. USE THIS WHEN someone asks what is coming: "which contracts in Queensland end in the next six months", "what is planned for ICT next quarter", "what is expiring for this buyer". `kind` is one of contract_expiry (a contract ending, with its incumbent
find_tenders ~864 tokens
Search open tenders across Australia; New Zealand rows only when you ask for them (jurisdiction=NZ). FREE, within the weekly cap. USE THIS WHEN someone asks what public-sector work is open: "any council drainage tenders in Victoria", "what's closing this month in NSW", "show me federal IT opportuni
get_warrant ~209 tokens
Retrieve a stored warrant by id (e.g. 'warrant_<hex>') — the full bundle as JSON, or a human-readable Markdown report when as_markdown=True. USE THIS WHEN you have a warrant_id from an earlier verify_document / check_document call and need the FULL evidence — every signal that fired, pe
match_tenders ~680 tokens
Rank open tenders against what a company actually does. Free, inside the weekly cap. USE THIS WHEN someone asks which opportunities suit a specific business: "what could we bid for", "is there anything for a civil contractor in Victoria", "find work for acme.com.au". Give `company_url`
screen_adverse_media ~630 tokens
Screen a person or organisation for ADVERSE MEDIA and SANCTIONS exposure (KYC/AML). PEP lists are not screened: `sanctions.flags.pep` is always false and `sanctions.note` says so. USE THIS WHEN onboarding or due-diligence asks: does this subject appear in negative news (fraud, money lau
submit_feedback ~218 tokens
Record thumbs up/down on a warrant's rating (the engine's precision-flywheel label source). verdict must be 'up' or 'down'; note is optional free text. USE THIS WHEN the ground truth became known after a verify_document call — e.g. the document was later confirmed genuine or fraudulent
tender_sources ~265 tokens
Every source we search, what it is allowed to do, and what the last run returned. FREE. USE THIS WHEN someone asks where the data comes from, whether a particular portal is covered, or why a search came back empty. It is the honesty surface: it names sources behind login walls, sour
verify_document ~504 tokens
Forensically inspect a document (PDF or image) for authenticity: tampering signs, AI-generation indicators, arithmetic reconciliation (financial docs), and provenance. USE THIS WHEN someone shares a payslip, bank statement, invoice, receipt, ID, certificate, or contract and asks: is thi
verify_identity ~443 tokens
Run an Australian identity check over a SET of identity documents. A vision model reads each document (which ID it is, which fields it shows — name/photo/address/signature — and its issue date); a deterministic engine then tallies them against a scheme and reports whether identity is est
verify_references ~596 tokens
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 cit

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