exa
Server Details
Fast, intelligent web search and web crawling.
New mcp tool: Exa-code is a context tool for coding
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- exa-labs/exa-mcp-server
- GitHub Stars
- 4,557
- Server Listing
- Exa MCP Server
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Tool Definition Quality
Average 4.5/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: web_search_exa is for discovering content via search queries, while web_fetch_exa is for extracting full content from known URLs. Their descriptions explicitly differentiate them and even mention when to use each (e.g., use web_fetch_exa after web_search_exa if highlights are insufficient). There is no ambiguity or overlap in functionality.
Both tools follow a consistent snake_case naming pattern with the prefix 'web_' and descriptive suffixes ('search_exa' and 'fetch_exa'). This makes them easily recognizable as part of the same set and clearly indicates their roles (searching vs. fetching) within the web domain.
With only 2 tools, the set feels thin for a web-related server, as it lacks operations like updating, deleting, or managing search history. However, the tools cover core search and fetch workflows effectively, making it borderline but functional for basic web content retrieval.
For a web search and content extraction domain, the tools provide search and fetch capabilities, which are essential. However, there are notable gaps, such as no tools for filtering results, saving searches, or handling errors (e.g., retrying failed fetches). The surface is minimal but covers the primary use cases without dead ends.
Available Tools
2 toolsweb_fetch_exaARead-onlyIdempotentInspect
Read a webpage's full content as clean markdown. Use after web_search_exa when highlights are insufficient or to read any URL.
Best for: Extracting full content from known URLs. Batch multiple URLs in one call. Returns: Clean text content and metadata from the page(s).
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | URLs to read. Batch multiple URLs in one call. | |
| maxCharacters | No | Maximum characters to extract per page (default: 3000) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds behavioral context by stating the return format ('Clean text content and metadata from the page(s)') and batching capability, which enhances transparency beyond the annotations.
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?
Extremely concise: three short sentences that front-load the core purpose and usage. Every sentence adds value without redundancy.
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?
Given the absence of an output schema, the description provides an adequate summary of returns ('Clean text content and metadata'). The tool is simple with few parameters, and the description covers the essential use cases and constraints.
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%, so baseline is 3. The description echoes batching advice already present in the schema for 'urls' but does not add new details about 'maxCharacters' or parameter constraints beyond the schema.
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 clearly states the action ('Read a webpage's full content as clean markdown') and the resource (webpage). It distinguishes from the sibling tool 'web_search_exa' by specifying when to use each: 'Use after web_search_exa when highlights are insufficient or to read any URL.'
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?
Provides explicit when-to-use guidance: 'Use after web_search_exa when highlights are insufficient or to read any URL.' Also mentions batching multiple URLs as best practice, giving clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
web_search_exaARead-onlyIdempotentInspect
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.| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural 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'. | |
| numResults | No | Number of search results to return (default: 10). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds behavioral context: returns clean text from top results, describes query tips, and suggests follow-up. It does not contradict annotations and provides useful additional behavioral traits.
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 concise at about 6 sentences, well-structured with sections for best use, returns, and query tips. Every sentence adds value without redundancy, and key information is front-loaded.
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?
Given no output schema, the description explains what is returned (clean text from top results). It covers main use cases, query formulation, and links to sibling tool. Some details like error handling or result formatting could be added, but it's sufficient for a search 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 coverage is 100% with both parameters described. The description adds significant value by explaining how to formulate queries (natural language, category syntax) and mentioning the default for numResults. This goes beyond the schema's basic descriptions.
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 clearly states the tool searches the web for any topic and returns clean, ready-to-use content. It distinguishes itself from sibling web_fetch_exa by focusing on search results and providing query tips, making its purpose unambiguous.
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 provides explicit guidance: best for current info, news, facts, etc.; query tips like describing the ideal page rather than keywords; category syntax for people/companies; and a follow-up suggestion to use web_fetch_exa for more details. This fully informs when and how to use the tool.
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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