Skip to main content
Glama

web_search_exa

Read-onlyIdempotent

Search the web for any topic and get clean, ready-to-use content.

  Best for: Finding current information, news, facts, people, companies, or answering questions about any topic.
  Returns: Clean text content from top search results.

  Query tips:
  describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue".
  Use category:people / category:company to search through Linkedin profiles / companies respectively.
  If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query. Should be a semantically rich description of the ideal page, not just keywords. Optionally include category:<type> (company, people) to focus results — e.g. 'category:people John Doe software engineer'.
numResultsNoNumber of search results to return (default: 10).

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds behavioral detail beyond the annotations: it returns clean text from top results, accepts natural-language queries, and supports category prefixes. This extra context is useful, though it does not discuss rate limits or pagination.

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 well structured with clear sections: a one-line purpose, best-for context, return value, and query tips. Every section earns its place, and the most important operational guidance is front-loaded. No fluff or repetition.

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

Completeness5/5

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

For a two-parameter, read-only search tool with no output schema, this description is complete enough: it explains what results look like ('clean text content'), how to formulate queries, how to use categories, and what to do when results are insufficient. The 'highlights' term is not defined, but the intended meaning is clear from context.

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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful query-formation guidance beyond the schema: 'describe the ideal page, not keywords,' a concrete example, and the category:people / category:company usage hints. That pushes it above baseline, though numResults receives no additional explanation beyond its schema default.

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 opens with a specific verb-resource combination ('Search the web for any topic and get clean, ready-to-use content') and further clarifies with 'Best for' and 'Returns'. It clearly separates this tool from the sibling web_fetch_exa by positioning itself as the search step and web_fetch_exa as the follow-up fetch step.

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

Usage Guidelines5/5

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

The description gives explicit usage context: 'Best for: Finding current information, news, facts, people, companies, or answering questions about any topic.' It also names the sibling and the condition for switching ('If highlights are insufficient, follow up with web_fetch_exa on the best URLs'), which qualifies as explicit when-to-use and when-to-alternative guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.5/5.0
Disambiguation5/5

web_search_exa is for discovering relevant pages via query, while web_fetch_exa retrieves full content from known URLs. The descriptions explicitly cross-reference each other, leaving no ambiguity about which tool to use.

Naming Consistency5/5

Both tools follow a consistent web_<action>_exa pattern. The verb-first structure clearly indicates the operation, and the shared suffix signals the server's branding.

Tool Count4/5

Two tools is slightly below the typical 3-15 range, but each tool earns its place and together they cover the core search-and-fetch workflow of the server. The minimal surface feels reasonable for this narrow domain.

Completeness5/5

The server provides the essential lifecycle for web research: search to discover relevant pages and fetch to read full content. There are no obvious missing operations for the stated purpose.