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Exa MCP Server

Exa MCP Server

by MrunmayS
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Remote

web_search_exa

Read-onlyIdempotent

Perform real-time web searches and scrape content from URLs using AI-powered search. Configure result counts and search types to find relevant information.

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

NameRequiredDescriptionDefault
queryYesWebsearch query
numResultsNoNumber of search results to return (default: 8)
livecrawlNoLive crawl mode - 'fallback': use live crawling as backup if cached content unavailable, 'preferred': prioritize live crawling (default: 'fallback')
typeNoSearch type - 'auto': balanced search (default), 'fast': quick results, 'deep': comprehensive search
contextMaxCharactersNoMaximum characters for context string optimized for LLMs (default: 10000)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv1.0.0
    • addedInput schema / properties / contextMaxCharacters
      Added value: +{
+  "description": "Maximum characters for context string optimized for LLMs (default: 10000)",
+  "type": "number"
+}
    • addedInput schema / properties / livecrawl
      Added value: +{
+  "description": "Live crawl mode - 'fallback': use live crawling as backup if cached content unavailable, 'preferred': prioritize live crawling (default: 'fallback')",
+  "enum": [
+    "fallback",
+    "preferred"
+  ],
+  "type": "string"
+}
    • changedInput schema / properties / numResults / description
      Previous value: -"Number of search results to return (default: 5)"New value: +"Number of search results to return (default: 8)"
    • changedInput schema / properties / query / description
      Previous value: -"Search query"New value: +"Websearch query"
    • addedInput schema / properties / type
      Added value: +{
+  "description": "Search type - 'auto': balanced search (default), 'fast': quick results, 'deep': comprehensive search",
+  "enum": [
+    "auto",
+    "fast",
+    "deep"
+  ],
+  "type": "string"
+}
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds valuable behavioral context beyond annotations: it mentions real-time web searches, scraping from specific URLs, configurable result counts, and returning content from relevant websites. This provides useful operational details without contradicting annotations.

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 appropriately sized at two sentences, front-loading the core purpose. Every sentence adds value: the first defines the tool's function, and the second elaborates on features and output. There's no wasted text, though it could be slightly more structured for optimal clarity.

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 moderate complexity, rich annotations (covering safety and idempotency), and 100% schema coverage, the description is reasonably complete. It explains the tool's function and key features. The lack of an output schema is a minor gap, but the description mentions return content, partially compensating. For a read-only search tool, this provides adequate context.

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 description coverage is 100%, so the schema fully documents all 5 parameters. The description adds minimal parameter semantics beyond the schema, mentioning only 'configurable result counts' (referencing numResults) and 'content from the most relevant websites' (hinting at query relevance). Since the schema does the heavy lifting, 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.

Purpose4/5

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

The description clearly states the tool's purpose: 'Search the web using Exa AI - performs real-time web searches and can scrape content from specific URLs.' It specifies the verb (search/scrape) and resource (web/URLs), making the function unambiguous. However, it doesn't explicitly differentiate from its sibling 'get_code_context_exa' beyond mentioning general web search capabilities.

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 usage for web searches and content scraping, but provides no explicit guidance on when to use this tool versus its sibling 'get_code_context_exa' or other alternatives. It mentions configurable result counts and relevance, which suggests some context, but lacks clear when/when-not directives or named alternatives.

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

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