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web3-agents-mcp

web3-agents-mcp

by hanjoonchoe
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_registration_file

Fetch and verify an AI agent's registration file from its token URI, confirming IPFS CIDs and data URIs while flagging unverifiable HTTPS links.

Instructions

Fetches and verifies an agent's registration file (via its tokenUri): ipfs:// CIDs are verified, data: URIs are inherently verified, https:// is unverifiable in v1 (no on-chain hash commitment).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agentId": "<agentId>"
    },
    "name": "get_registration_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
chainNoChain to query, by name (see list_chains). Defaults to base.
agentIdYes
requireVerifiedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses important behavioral details: verification depends on URI scheme (ipfs verified, data inherently verified, https unverifiable). This is beyond a simple 'fetches file' statement. However, it doesn't mention output format, error behavior, or whether the tool performs network requests.

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 a single, information-dense sentence that front-loads the action and provides key verification details. Every word earns its place; there is no redundancy or filler.

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

Completeness3/5

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

The core function and verification criteria are described, but with no output schema and no annotations, the description should explain what the tool returns and any prerequisites. It does not, leaving gaps in return format and parameter usage. It is adequate for a simple fetch tool but not fully complete.

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

Parameters2/5

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

Schema coverage is only 33% (chain has description, agentId and requireVerified do not). The description mentions 'via its tokenUri' but doesn't explain the parameters. agentId is inferable from the name, but requireVerified's behavior is not clarified. The description does not compensate for the low 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 the tool's action: 'Fetches and verifies an agent's registration file'. It specifies the resource and the verification behavior, distinguishing it from sibling tools like resolve_agent which likely resolves agent metadata, and trust assessment tools.

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 provides clear context for when to use this tool: when you need to fetch and verify a registration file. It also notes that https:// URIs are unverifiable in v1, which is a limitation but not an explicit alternative. It doesn't explicitly compare to sibling tools, but the purpose is unambiguous.

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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