Exa Websets MCP Server

web_search_exa

Perform real-time web searches and extract content from URLs using Exa AI, with customizable result counts.

Instructions

Search the web using Exa AI - performs real-time web searches and can scrape content from specific URLs. Supports configurable result counts and returns the content from the most relevant websites.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "web_search_exa"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Search query
`numResults`	No	Number of search results to return (default: 5)

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.0.0Jan 3, 2026
- addedInput schema / $schema
```
Added value: +"http://json-schema.org/draft-07/schema#"
```
- addedInput schema / additionalProperties
```
Added value: +false
```
First observedDec 2, 2025

TDQS

A3.6/5.0

Behavior3/5

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

No annotations exist, so the description carries full burden. It discloses real-time searching and scraping but lacks details on authentication, rate limits, or behavior when no results. The description is adequate but not comprehensive.

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 two sentences, no fluff, covering the main behavioral aspects. It is well-structured but could be slightly more organized (e.g., separate lines). Still, it is efficient.

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

Completeness3/5

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

For a 2-parameter tool with no output schema or annotations, the description covers primary functionality and return content. However, it omits details like scraping mechanics, error handling, and data freshness. Adequate but not fully 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 coverage is 100%, so baseline is 3. The description adds 'configurable result counts' (aligning with numResults) and mentions scraping, which is not reflected in parameters. Some extra context but not significantly beyond schema.

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 performs real-time web searches using Exa AI and can scrape content from specific URLs. It distinguishes itself from sibling tools (knowledge_graph, websets_guide, websets_manager) which are not general web search tools, making purpose unambiguous.

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

Usage Guidelines3/5

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

The description implies this is the general web search tool but does not explicitly state when to use it versus alternatives like knowledge_graph or websets_guide. No when-not-to-use or exclusion criteria are provided.

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

Deploy Server