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Tanod MCP server

agentscan: identify an x402 client by User-Agent: monitor, indexer, grader or HTTP library

identify_x402_client
Read-onlyIdempotent

Identify whether a User-Agent is a known x402 monitor, indexer, grader, SDK, bot, or HTTP library, and return its role and observed call rate at one seller.

Instructions

agentscan: Identify an x402 client by User-Agent: monitor, indexer, grader or HTTP library, with call rate. For any other User-Agent use parse_user_agent; for a whole access log use analyze_agent_traffic. Returns whether a User-Agent is a known x402 monitor, indexer, grader, SDK, AI fetcher, bot or HTTP library, what it does and its observed call rate at one seller (requests a day, per route, unpaid share); no ua: the full table. Input: optional ua; GET takes it as a query parameter. Reviewed table from one seller's logs and public docs; observed kinds are not confirmed by the operators. Unknown is known false (charged). The ua is not stored. Typically under 0.1 s. Price: USD 0.001. Free: 10 agent-index calls per IP per UTC day. Docs: https://tanod.dev/learn/x402-mcp-server-directory-api.html

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uaNoOptional: a User-Agent string to identify (at most 512 characters; not stored or echoed). Empty or absent: the whole table.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo
noteNo
countNo
errorNoOnly on an error result: an object {code, message}, or the reason string of an x402 PaymentRequired object.
kindsNo
knownNo
clientNo
methodNo
clientsNo
versionNo
kind_meansNo
matched_byNo
family_labelNo
product_tokenNo
observed_windowNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent/openWorld annotations: discloses that the ua is not stored or echoed, that unknown results return known=false and are still charged, that observed kinds are unconfirmed by operators, plus latency (~0.1 s), price, and a free-tier limit. This is rich behavioral context an agent could not infer.

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

Conciseness4/5

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

Front-loads the core purpose and alternatives before the return-value, pricing, and docs details. It is dense and somewhat long, with the title text replayed at the start, but nearly every sentence carries distinct information.

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?

Despite an output schema existing, the description adds the semantic frame (known/unknown, call-rate meaning, seller-scope caveat) an agent needs to interpret results, plus pricing and docs. For a 1-param read tool this is complete.

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

Parameters4/5

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

Schema coverage is 100% and already documents the single optional `ua`, so baseline is 3. The description adds value beyond the schema by noting that the GET transport takes it as a query parameter and that empty/absent input yields the whole table, though it restates the 512-char/no-store details already in the schema.

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?

States a specific verb (identify) and resource (an x402 client by User-Agent), and names the exact categories it resolves (monitor, indexer, grader, HTTP library). It explicitly distinguishes itself from siblings parse_user_agent and analyze_agent_traffic, so an agent can route without opening a schema.

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

Usage Guidelines5/5

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

Gives explicit when-to-use alternatives: 'For any other User-Agent use parse_user_agent; for a whole access log use analyze_agent_traffic,' and clarifies the no-`ua` case returns the full table. Boundaries against siblings are fully specified.

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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