Token due-diligence (bundle) — One call to vet an ERC-20 token on Base or Ethereum: live USD price, holder count, and security signals (honeypot, mintable, open-source, buy/sell tax, owner & holder concentration) fused into a risk verdict. JSON. Price: $0.10 USDC (Base, via x402).
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | base or ethereum (default base) | |
| address | Yes | token contract address (0x…) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: it returns JSON, supports Base and Ethereum, and costs $0.10 USDC via x402. This goes beyond the annotations without contradicting them.
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 a single dense sentence that front-loads the core purpose, then lists key outputs, output format, and pricing. Every clause adds useful information, with no filler or redundancy.
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?
The description covers the invocation context, supported chains, expected outputs, output format, and cost. There is no output schema, so the high-level output list is sufficient. Minor gaps like the exact risk-verdict scale are not critical for calling the tool correctly.
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%, so the schema already explains 'address' and 'chain' fully. The description mentions Base and Ethereum and token contract address, but these add little beyond the existing schema descriptions. Per the baseline for high coverage, a 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 opens with a clear verb ('vet') and a specific resource ('an ERC-20 token on Base or Ethereum'), then enumerates the concrete outputs: live USD price, holder count, and security signals fused into a risk verdict. This distinguishes it from sibling tools like crypto_balance or crypto_gas, which address different needs.
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 provides clear usage context: 'One call to vet an ERC-20 token' signals exactly when to invoke this tool. It does not explicitly name alternatives or state when not to use it, but the context is specific enough that an agent can select it correctly for token due-diligence tasks.
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.
Many tools are clearly separated by prefix and data source, but several bundled products overlap heavily: vehicle_deal_check vs vehicle_report, realestate_property_report vs realestate_site_risk, finance_company_360 vs finance_health_scan, and domain_due_diligence vs email_domain_check/business_vet. An agent would frequently struggle to pick the correct premium bundle.
Tool names overwhelmingly follow a consistent snake_case category-prefix pattern like weather_, crypto_, vehicle_, finance_, and geo_. Minor deviations such as bare names (domain, ip) and noun-verb forms (dns_lookup, url_check) are easy to learn and don't create real confusion.
50 tools is far beyond the typical well-scoped 3–15 range and will require heavy filtering to navigate. The broad multi-domain data marketplace partially justifies the size, but it would be more coherent split into per-domain servers or consolidated further.
For a read-only data/diligence marketplace, the surface is quite comprehensive: weather, vehicle, crypto, SEC/finance, domain/email, sanctions, and geo workflows all have core operations plus fused verdict bundles. Minor gaps exist—such as a simple crypto price lookup or vehicle market value—but agents can usually work around them.