data_token_supplyTotal/circulating/burned supply and burn percentage for an ERC-20 on Base. $0.003 per call.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | ERC-20 token contract address on Base (0x-prefixed, 42 chars) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this a read-only, idempotent, non-destructive operation, so the description does not need to repeat safety traits. It adds only the $0.003 per call pricing, but it does not disclose call behavior such as output format, network edge cases, or any data freshness caveats.
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 short sentences with no redundancy. The core metric set is front-loaded, and the pricing note is separated and useful.
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 one-parameter read-only tool, the description covers the tool's purpose, the key returned values, and cost, while the schema documents the address. A minor gap is that it does not explicitly describe the response container or edge cases, but the tool is simple enough that it remains sufficiently complete.
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?
The schema already provides 100% coverage for the single address parameter, including its format on Base. The description adds no extra parameter semantics, so the baseline 3 is appropriate.
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 identifies the resource (ERC-20 token supply data on Base) and the specific metrics returned (total, circulating, burned supply and burn percentage). It is distinct in content, but it does not explicitly differentiate itself from sibling data_* tools, so it stops short of a 5.
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 description implies the tool should be used when an agent needs ERC-20 supply and burn metrics on Base. However, it provides no explicit when-not-to-use guidance and does not name any alternative sibling tools, so the routing decision is left largely to inference.
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.