# Exa

> The search engine built for AIs — semantic web search, page contents, Websets, and research APIs, plus the ecosystem's most-used search MCP server.

Exa is a search engine designed for AI consumers, not human browsers: a semantic Search API with deep-search profiles, a Contents API returning clean page text and summaries, Websets for building enriched entity sets, and research endpoints. Its hosted MCP server (mcp.exa.ai/mcp) is the most-used search server in the ecosystem and even works keyless on a rate-limited free tier.

Website: https://exa.ai

Exa is what search looks like when the customer is an agent: **semantic search in, clean text out.** Where Google optimizes for a human scanning ten blue links, Exa's Search API returns machine-ranked results and its Contents API hands back the page as clean text, highlights, or AI summaries — the retrieval layer for agents and RAG pipelines, sold as an API.

## Highlights

- **Search built for LLM consumption** — neural/semantic search with speed/quality profiles up to Deep Search and deep-reasoning modes for research-grade queries.
- **Contents, not links** — clean page text, highlights, and summaries per result; structured outputs via an `output_schema` parameter.
- **Websets** — build and enrich entity sets ("every Series-B devtools company and their CTOs") as a product, not a scraping project.
- **Research & Monitors** — multi-step research runs and standing watches on a query, exposed as API products.
- **The most-used search MCP server** — hosted at `mcp.exa.ai/mcp`, MIT-licensed, with keyless rate-limited access for instant trial.

## In an AI-assisted workflow

```bash
claude mcp add --transport http exa https://mcp.exa.ai/mcp
# keyless works (rate-limited); add x-api-key from dashboard.exa.ai for real use
# then:
# > Research how teams are handling MCP server auth in production —
# > search broadly, fetch the three best sources, and synthesize
```

The MCP toolset is deliberately small after a 2025–26 consolidation: `web_search_exa` and `web_fetch_exa` by default, plus an opt-in advanced-search tool with filters. (Older tutorials referencing `linkedin_search_exa` or `deep_researcher_*` tools are out of date — those folded into the core tools and the Research API.)

> [!TIP]
> Exa pairs with [Firecrawl](/tools/firecrawl) as the two halves of agent web-data: Exa finds the right pages; Firecrawl extracts at depth and scale from sites you already know. Plenty of agent stacks run both.

## Good to know

Exa Labs raised an $85M Series B (Benchmark, announced September 2025) — the "search engine for AIs" thesis is well-funded and the API surface is moving fast. Pricing is freemium: a monthly free allowance, then metered pay-as-you-go per product tier; enterprise adds zero-data-retention. Like any web-content tool, what it fetches enters your agent's context — treat retrieved pages as untrusted input in [injection-sensitive setups](/guides/ai-safety/defending-prompt-injection).

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_Source: https://agentscamp.com/tools/exa — Tool on AgentsCamp._