Skip to main content
Glama
superagents-lab

Search1API MCP Server

Search the web

search
Read-only

Retrieve current information from the public web with citable results including title, URL, and text. Optionally fetch full pages and filter by time or source.

Instructions

Search the live public web when the user needs current information, sources, or research. Returns citable results with id, title, URL, and text. Pass a result id to fetch to retrieve the full page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesShort, focused search query
time_rangeNoOptional recency window for time-sensitive searches
max_resultsNoMaximum number of results to return
crawl_resultsNoNumber of top results to retrieve as full pages. Each successful page retrieval adds 1 credit to the base 1-credit search request
exclude_sitesNoDomains to exclude from the search
include_sitesNoDomains to include when the user explicitly scopes the search
search_serviceNoSearch engine to use; choose one only when it matches the user's source intentgoogle

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYes
Behavior5/5

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

Annotations already indicate read-only behavior, but the description adds valuable context about credit costs for crawling results and the workflow of fetching full pages. No contradictions.

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 purpose, and each sentence adds essential information. No redundancy.

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 the tool's complexity (7 parameters, output schema), the description covers the search purpose, result format, and interaction with fetch. It does not discuss error handling or rate limits, but is largely sufficient.

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

Parameters4/5

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

The input schema has 100% parameter description coverage. The description adds extra behavioral context, such as the credit cost for crawl_results and guidance that include_sites should only be set when the user explicitly scopes the search.

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

Purpose5/5

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

The description clearly states the tool searches the live public web for current information, using a specific verb and resource. It explains the output format and the interaction with the fetch tool, which distinguishes it from sibling tools like fetch and news.

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?

It provides explicit context for when to use the tool ('when the user needs current information, sources, or research'). It hints at alternatives by mentioning fetch for full pages, but does not explicitly state when to avoid this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/superagents-lab/search1api-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server