| name | build-with-exa |
| version | 0.1.0 |
| description | Build applications and agents with Exa's API Platform: search, contents, answer, context, Agent API, monitors, websets, OpenAI-compatible endpoints, and exa-py / exa-js. Use when choosing Exa endpoints, writing Exa API calls, integrating semantic web search or research into products, or debugging Exa request shapes. Load references/ on demand for endpoint details.
|
| allowed-tools | ["Bash","Read","Write","Edit","Skill"] |
| author | Exa Labs (ported by mktg) |
| license | MIT |
| user-invocable | true |
| metadata | {"openclaw":{"emoji":"🧩"}} |
On Activation
- Confirm
EXA_API_KEY is available for any live API call. SDK examples assume the key is set.
- Default new integrations to
POST /search with type: "auto" and contents.highlights: true. Escalate to Agent API only for multi-step research / list-building.
- Load only the
references/*.md file needed for the current endpoint - do not dump the whole tree into context.
- For agent-native marketing research inside mktg projects, prefer
exa-search, company-research, or lead-generation over inventing a custom integration.
Build with Exa
Scope
Included by default:
- Core retrieval APIs: search endpoint, contents endpoint, answer endpoint, context endpoint
- Long-running research workflows: Agent API (
/agent)
- Async and recurring workflows: Monitors API, Websets API
- SDK guidance: Python
exa-py, TypeScript exa-js
Note on data retention: /search, /answer, and deep research are Zero Data Retention (ZDR). The Agent API (/agent), Websets, and Monitors are not ZDR. If a use case requires ZDR, stay on the ZDR surfaces or contact Exa.
Installation
pip install exa-py
npm install exa-js
Authentication
export EXA_API_KEY="your_api_key_here"
Exa accepts either the x-api-key header or Authorization: Bearer <key>.
API Decision Workflow
Before picking an endpoint, decide which workflow shape fits:
- Raw web content for your own LLM or agent: start with
/search using type: "auto" and contents: { highlights: true }
- Synthesized structured output: start with
/search using the search type that fits your latency and reasoning needs, then add outputSchema and systemPrompt
- Long-running multi-step research, list-building, or enrichment with structured output: use the Agent API ()
