verify_tokenIs this the real USDC/EURC/WETH/cbBTC/USDT on Base? Anti-phishing for stablecoin payments. $0.005 per call.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Token contract address (0x…) or symbol (e.g. USDC, WETH) to verify against the canonical Base list |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already disclose read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context: it checks against a canonical list, targets specific assets, and costs $0.005 per call. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no fluff. The core purpose is front-loaded in the question, and the pricing detail is the only extra but relevant piece of information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read-only verifier with comprehensive annotations, the description is largely complete. The only minor gap is that it does not explicitly state the return format, though the question format strongly implies a yes/no verification result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the query parameter is clearly documented as a contract address or symbol. The description itself adds no further parameter detail, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool verifies whether a token is the canonical USDC/EURC/WETH/cbBTC/USDT on Base, giving a specific resource, network, and asset set. The title 'Canonical token check (Base)' reinforces the scope and distinguishes it from generic token or payment tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Anti-phishing for stablecoin payments' provides clear contextual guidance on when to use the tool. It does not explicitly name sibling alternatives or state when not to use it, but the stablecoin-payment context is strong enough for an agent to route correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are cleanly separated by domain prefix (data_, security_, validate_, verify_) and describe distinct outputs. A couple of pairs like token_verdict vs verify_token or data_portfolio vs wallet_dossier could be confused until descriptions are read, but the descriptions resolve the ambiguity.
The majority of tools follow a predictable prefix_subject pattern, e.g. data_block, security_tls, validate_iban, verify_payment. A few outliers like html_to_markdown, text_diff, wallet_dossier, and token_verdict use different conventions, but the overall system remains readable.
20 tools is on the heavy side for the typical MCP server and sits in the 16–25 'feels heavy' zone. Most tools have a legitimate purpose, but the five validate_* identifier tools plus two generic utilities could feel like surface area bloat.
The server covers a broad and coherent read/validation domain: chain data, token safety, payments, security checks, and identifier validators. Minor gaps exist, such as lack of detailed historical transaction/activity data and no general network/domain security scan beyond email, TLS, and typosquat.