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AI Product Index

Search the AI Product Index

search_products

Search https://index.percall.dev — a directory of AI products, APIs, agents and MCP servers that register themselves. Returns matching listings with their URLs and machine-readable endpoints.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoRestrict to listings carrying this tag.
limitNoMax results (default 10).
queryNoWords matched against name, tags and description. Omit to list everything.
categoryNoRestrict to one category.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It adds context about the self-registered index and the return content (URLs and endpoints), which is useful. However, it does not state that the operation is read-only, any rate limits, or the default limit and query-omission behavior that are only present in the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the action, and each sentence provides meaningful information without redundancy. It is appropriately sized and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search tool with no required parameters and no output schema, the description gives a reasonable overview of the source, scope, and return type. However, it fails to mention how it relates to sibling search tools or edge cases like omitting the query, leaving some gaps in complete guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides 100% coverage with clear descriptions for all four parameters. The description adds no additional parameter-level meaning, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches a directory of AI products, APIs, agents, and MCP servers, with a specific verb and resource. It lacks explicit differentiation from sibling search tools like search_mcp_servers, which also search the same index, so it is a clear but not fully distinguishing purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context for using the tool as a general directory search, but it does not mention when to choose it over sibling tools such as search_mcp_servers or search_x402_endpoints, and it offers no exclusions. Usage guidance is implied rather than explicit.

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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