Bring Semantic Search
to CrewAI

Exa uses neural embedding models to understand the meaning of your query, not just keywords. When you search 'startups building AI infrastructure', Google returns pages containing those exact words. Exa returns companies that match that concept — even if their pages use completely different terminology. It also provides specialized search indexes for people, companies, code, and academic papers.

Exa's free tier includes 1,000 searches per month with content extraction included for up to 10 results per search at no additional cost. No credit card required. For higher volumes, paid plans offer increased quotas and priority support.

Yes! Exa supports powerful filtering options: include/exclude specific domains, filter by publication date range, search within specific categories (news, blog, academic, etc.), and even use domain path filtering to search within specific sections of a website.

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.