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Search checked remote MCP endpoints

search_mcp_directory

Search remote MCP endpoints from external public registries, including the status Licium recorded when checking them. These are not Licium bounty agents. An entry that needs a key, does not answer, or was not found can be asked for as a build with request_source. When query matches nothing on the first page, data.next says what to do: ask_for_it (request_source with the same words), open_pot (the open bounty for the same words, with its pledge_url) when one exists, and post_bounty (bounty_post).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoExact normalized endpoint URL.
limitNoMax endpoints to return (default 10, max 20).
queryNoSearch endpoint name or hostname.
cursorNoOpaque cursor returned by the previous page.
statusNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. Added

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does explain that entries can have statuses like needing a key, not answering, or not being found, and it mentions data.next behavior for empty results. However, it doesn't cover authentication requirements, rate limits, or whether this is a read-only operation. The behavioral context is partial but useful.

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

Conciseness4/5

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

The description is front-loaded with the core purpose and then provides usage guidance in a structured manner. It is efficient and avoids unnecessary repetition, though the sentence about data.next is somewhat dense and could be clearer. Overall, it earns its place without being verbose.

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

Completeness4/5

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

Given no output schema and no annotations, the description does a good job of explaining the tool's behavior, including what statuses mean and how to handle empty results via data.next. It covers the main use cases and edge conditions. However, it could be more complete by mentioning pagination behavior (cursor) or authentication needs, but for a search tool with 80% schema coverage, this is reasonably complete.

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?

Schema description coverage is 80%, so most parameters are documented in the schema. The description adds value by explaining the response behavior (data.next) rather than parameter details. It doesn't provide additional semantics for parameters like url, limit, or status beyond what the schema already covers. Baseline 3 is appropriate given high schema coverage.

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 a specific verb+resource: searching remote MCP endpoints from external public registries with status information. It distinguishes from siblings by noting 'These are not Licium bounty agents,' which helps differentiate from bounty-related tools. However, it could be clearer about what makes this distinct from other search or list tools.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool and how to handle edge cases. It explains what to do when an entry needs a key, doesn't answer, or isn't found (use request_source), and what data.next provides when no matches are found. This is helpful guidance, though it doesn't explicitly name alternative tools for searching in different contexts.

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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