Search the live web, retrieve top results, and receive clean markdown content ready for AI processing. This tool converts search results into structured text for RAG pipelines and agents.
Searches the live web and retrieves extracted markdown content from the top results.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of search results to return (default: 5). | |
| query | Yes | The search query to execute on the web. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full behavioral disclosure burden. It does add value by stating that output is extracted markdown content and that only top results are returned. It does not disclose limits, rate behavior, error cases, or whether the returned content is truncated, but the core behavior is transparent enough for a simple search tool.
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 a single sentence that leads with the primary action and packs the key output characteristic into a compact statement. Every word earns its place, and there is no redundant filler.
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?
For a low-complexity tool with two well-described parameters, the description covers the purpose and general output type. However, there is no output schema and the description does not specify the exact result structure, such as whether each result includes a title or URL alongside the markdown, or how results are ordered. This leaves some ambiguity for an agent invoking the 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%, with clear descriptions for both 'query' and 'limit'. The tool description adds general output context but no parameter-specific detail beyond what the schema already provides, so the baseline 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 ('Searches') and identifies a clear resource ('the live web'), with a concrete outcome ('retrieved extracted markdown content from the top results'). It is distinguishable from siblings like flycrawl_scrape because it centers on search rather than a specific page, though it does not explicitly name those alternatives.
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 when to use the tool: when you need live web search results with markdown content. However, it provides no explicit guidance on when not to use it or which sibling tool to prefer, leaving the agent to infer the boundary between search and the other flycrawl tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.