Queries a public Google Patents page for grant metadata without a key, with the official PatentsView Search API used when PATENTSVIEW_API_KEY is configured for richer structured data.
| Name | Required | Description | Default |
|---|---|---|---|
| patent_number | Yes | Patent number (e.g. 10000000) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It reveals the key behavioral trait of dual-mode operation (public page vs. PatentsView API) and implies a read-only operation. However, it does not cover error responses, rate limits, or authentication details.
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?
Two sentences, no wasted words. The description is front-loaded with the core purpose and efficiently conveys the dual-mode behavior.
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 no output schema and low complexity (1 parameter), the description covers what the tool does but lacks information about return format, error handling, or what 'grant metadata' entails. The agent may not know what to expect in the response.
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 description adds limited value beyond the schema. It provides an example and the phrase 'grant metadata' gives context, but does not elaborate on parameter format or validation.
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?
Description clearly states the tool queries a public Google Patents page for grant metadata and optionally uses the PatentsView Search API for richer data. The verb 'Queries' and resource 'Google Patents page' are specific, and the dual-mode behavior distinguishes it from any sibling 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 description implies usage generally for patent grant metadata and explains two modes based on API key configuration, but does not explicitly state when to use this tool over alternatives or any prerequisites beyond the key.
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 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.