search_toolsFind tools by natural-language query and return matching definitions ranked by relevance, so you can identify the right tool without browsing a full list.
Search for tools using natural language.
Returns matching tool definitions ranked by relevance, in the same format as list_tools.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language query to search for tools |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It usefully discloses the ranking behavior ('ranked by relevance') and the return shape, but says nothing about matching semantics (lexical vs semantic), result limits, or whether the search space covers all registered tools.
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 short sentences with no filler, and the core action is front-loaded before the return-format note. Slightly more structure (e.g. a single sentence) would be equally clear.
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?
An output schema exists, so return values need not be explained, and the single parameter is fully documented. What remains missing is routing context: an agent cannot tell from this description when to search for a tool rather than directly invoke call_tool.
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% for the single 'query' parameter, so the schema already explains it. The description's 'natural language' phrasing adds only marginal semantics beyond the schema and gives no guidance on query formulation or specificity.
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?
States a specific verb and resource ('Search for tools') and adds the input modality ('natural language'), which is more than a restatement of the name. However, it never distinguishes itself from sibling call_tool, which is the obvious competing path for an agent that already knows which tool to invoke.
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 reference to 'the same format as list_tools' implies this is a filtered alternative to a full listing, but list_tools is not among the provided siblings, so that anchor may not resolve for the agent. No explicit when-to-use or when-not-to-use guidance is given relative to call_tool or the research_* tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.