Locates the combined sales tax rate (state, county, local) for a US ZIP code using Ziptax, with Zippopotam used only for location enrichment. Matches: sales tax rate calculator, zip code tax lookup, commercial sales tax checker, e-commerce tax estimator, state county city tax rates.
| Name | Required | Description | Default |
|---|---|---|---|
| zip_code | Yes | 5-digit US ZIP code |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions using Ziptax and Zippopotam but does not specify traits such as whether it is read-only, rate limits, accuracy, or how missing ZIP codes are handled. This lack of disclosure leaves the agent with insufficient information.
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 concise with two sentences and a list of keywords. It front-loads the core purpose and key details. The list of matches could be seen as slightly redundant, but overall it is well-structured and efficient.
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?
Given the lack of an output schema and annotations, the description should provide a fuller picture of what the tool returns and handles errors. It omits return format, edge cases, and any side effects. This leaves the tool definition incomplete for an agent to use reliably.
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 fully describes the 'zip_code' parameter as a '5-digit US ZIP code' with examples. The description does not add new parameter-level details beyond stating the output context (combined rates). With 100% schema coverage, a score of 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 uses a specific verb 'locates' and identifies the resource as 'combined sales tax rate (state, county, local) for a US ZIP code'. It also lists matching search keywords, making the purpose very clear. The sibling tools list contains no similar tax tools, so no confusion arises.
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 a list of matching use cases (e.g., 'sales tax rate calculator'), but lacks explicit guidance on when to use this tool versus alternatives. Since no direct sibling tax tools exist, the omission is less critical but still a gap in providing clear usage boundaries.
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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Many tools have overlapping functionality, e.g., auditNetworkHost combines DNS, SSL, and header checks that have dedicated tools (auditDnsSecurity, checkSslExpiry, auditSecurityHeaders). Multiple weather and blockchain tools also overlap in scope, making it difficult for an agent to choose the right tool.
Most tools follow a consistent verb_noun pattern (e.g., getAirQuality, checkDnsPropagation), but a few deviate (agentPreflight, capabilitiesDiff) and some use compound names (depositCoordinationBounty). Overall, the pattern is clear but not perfectly uniform.
With 56 tools, the server is far too large for a coherent MCP surface. The number suggests a collection of many unrelated APIs rather than a focused tool set. A typical well-scoped server has 3-15 tools.
While the tool set covers many domains, each domain has shallow coverage. For example, blockchain tools miss basic transaction sending and contract deployment; weather tools lack forecasts. The 'requestMissingData' endpoint acknowledges gaps, but the current surface is severely incomplete for a general-purpose API.