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Riley Craig x402 Agent Store

by io.github.rccola990-cloud

chain_nft_owner

$0.09 via x402: who owns an NFT right now and where its metadata lives — ownerOf, tokenURI, collection name and symbol in one call, with the tokenURI classified as ipfs / on-chain data URI / http so you know how to fetch it. Read from the contract, so it is correct for tokens minted seconds ago and collections no marketplace has indexed. Base, Ethereum, Optimism, Arbitrum, Polygon, Gnosis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNobase|ethereum|optimism|arbitrum|polygon|gnosis (default base)
contractNoERC-721 contract address (0x...)
token_idNoToken ID (decimal or 0x hex)
x_paymentNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries full behavioral burden. It discloses that the tool reads from the contract (read-only), returns classified tokenURI types (ipfs/on-chain/http), and includes pricing ($0.09 via x402). It does not detail error handling or response format, but the core behavior is well communicated.

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

Conciseness5/5

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

The description is compact yet information-dense, front-loading the core purpose and cost, then explaining the on-chain advantage and supported chains. Every clause serves a purpose, and it is easy to scan.

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

Completeness4/5

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

For a read-only NFT lookup with no output schema, the description covers the key aspects: what data is returned, the source (contract), the freshness benefit, and supported chains. It stops short of describing the exact response shape or error cases, but overall it is complete enough for an agent to invoke correctly.

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

Parameters3/5

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

Schema description coverage is 75%, with chain, contract, and token_id already described. The description adds some value by listing supported chains and emphasizing token ID flexibility (decimal/hex), but x_payment remains undefined and no further parameter detail is provided. The baseline of 3 is appropriate given high schema coverage.

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?

The description clearly states what the tool does: determines NFT ownership and metadata (ownerOf, tokenURI, collection name/symbol) in one call. It specifies the resource (NFT on a given contract) and distinguishes itself from sibling chain tools by focusing on NFT-specific data.

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?

The description implies when to use this tool: when you need current on-chain data, 'correct for tokens minted seconds ago and collections no marketplace has indexed.' It does not explicitly name alternatives or exclusions, but the freshness angle provides clear context for selection.

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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TDQS

C2.7/5.0
Disambiguation2/5

Many tools occupy the same conceptual space: web_scrape vs markdown_web_scraper, post_check vs brand_ai_visibility_check, llm_chat_completions vs post_api_v1_chat_completions, chain_transaction_status vs chain_confirmations, and connect_token vs token_security_check + dex_token_data. Descriptions help in places, but for an agent facing 92 tools these near-overlapping endpoints will frequently cause misselection.

Naming Consistency2/5

Everything is snake_case, but the conventions diverge sharply: get_chain_* and chain_* coexist for the same RPC family, post_* names are HTTP-route artifacts, api_generate reverses noun_verb order, and many names are bare nouns rather than verb_noun. There is no predictable naming pattern an agent can rely on.

Tool Count1/5

At 92 tools this is far beyond the range where an agent can keep the surface coherent, even for a store. The flat tool list mixes products, bundles, aliases, proxies and single-use verticals, so most of the count is noise for any given task. A catalog/search/payment model with fewer exposed tools would fit the storefront purpose better.

Completeness3/5

The server has impressive breadth and covers key storefront/market workflows: catalog, samples, credits, directory listing, notary, and the task lifecycle. But each domain is shallow: there is no chain transaction broadcast, no task update/cancel/dispute, no AI-visibility history, and many verticals are a single tool with no follow-on operation. The surface is broad but not deeply complete.

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