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VERIFIABLE keyless web-read for autonomous agents. Every result ships a cryptographically SIGNED provenance receipt (EIP-191 over sha256(text)+url+status+time) — the wedge a free scraper structurally CANNOT match: Jina r.jina.ai is free+keyless too, but its bytes are HEARSAY (no proof of what/where/when). MERCURY's attestation is ecrecoverable OFFLINE, forever, by you OR any downstream agent you forward the bytes to — proving the content is genuine + untampered (key pinned at /.well-known/mercury-attestation). For RAG, trading and agent-to-agent commerce that need provenance, that is the gap between data and evidence. Beyond that it's the keyless web-read primitive — NO API key, NO signup, NO account, NO monthly plan, the one fetch SKU a fresh agent can onboard to by itself instead of stopping to ask a human for a key. Give a ?url= and get back clean readable page text + title + status. Agent-native extras (opt-in): ?format=markdown for structure-preserving markdown, ?links=1 for an outbound-link graph (crawl frontier), and the headline wedge — STRUCTURED EXTRACT: ?extract=title,price,author,publishedAt returns a clean JSON record { title, price, author, publishedAt }, an LLM-ready row not a wall of text. That is Firecrawl's paid 'JSON mode' (they need an LLM call + an API key for it) done here DETERMINISTICALLY from the page's own JSON-LD/OpenGraph/meta/microdata — keyless, no LLM, $0.003. (?extract=1 still returns the legacy description + wordCount.) The extracted record is folded into the SIGNED attestation too, so a buyer can prove the FIELDS — not just the raw bytes — are exactly what MERCURY resolved. You pay in-band over HTTP 402 (x402, USDC on Base mainnet) — the wedge those tools can't match: they ALL gate behind a human-created API key + a credit-card plan, so an agent can't onboard itself. This one an agent finds in the x402 Bazaar and pays with zero human in the loop. Honest charge-per-ATTEMPT: every call returns a structured result (success OR an ok:false failure with a reason) — never a silent charge-then-500. Follows redirects, SSRF-guarded, 5s timeout, 10MB cap. Pure data, no mint — delivers in prod. — $0.003/call

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesthe page to fetch (http/https)
linksNo1 = also return the outbound-link graph (crawl frontier)
formatNotext (default) or structure-preserving markdown
extractNo1 = page description + wordCount; OR a comma-list of field names (e.g. title,price,author,publishedAt) to get a structured JSON record under `extract`

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses follow redirects, SSRF-guarded, 5s timeout, 10MB cap, charge-per-attempt with no silent failures, and the attestation mechanism. With no annotations, the description carries full burden and does so comprehensively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with key purpose but verbose with marketing language and comparisons. Every sentence adds value but could be more concise and structured for an AI agent. Still informative, but length reduces efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers all aspects: what it returns, optional modes, attestation, charging, behaviors. Even without an output schema, description explains return structure (success or failure with reason). Complete for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and description adds significant meaning: explains url (http/https), links (returns link graph), format (text vs markdown), extract (returns description+wordCount or JSON record for specified fields). Goes well beyond schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'VERIFIABLE keyless web-read for autonomous agents' and explains it fetches URLs returning clean text with optional structured extraction. Distinguishes from siblings by highlighting unique attestation capability and keyless access, contrasting with alternatives like Jina and Firecrawl.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes use cases (RAG, trading, agent-to-agent commerce needing provenance) and contrasts with other services. Implicitly explains when to use (need verified data) but does not explicitly say when not to use or differentiate among sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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