Nango helps AI applications access external data and APIs. It is commonly used to:
  • Ingest data from 400+ APIs for Retrieval-Augmented Generation (RAG)
  • Enable AI agents to take actions via API calls

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AI agent demo video

Watch a video demo showing how to use Nango to power AI integrations:
If you want to run the demo yourself or check the code, here is the demo’s GitHub repo.

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Data ingestion for RAG

For applications that require fresh external data:
  • Continuous polling across 400+ APIs
  • Real-time ingestion via high-frequency syncing and webhooks
  • Full control over integration code for custom data processing

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API access for AI agents

For agents that interact with external APIs:
  • Instant access to 400+ APIs and 600+ use cases
  • Managed authentication (OAuth, API keys, etc.)
  • API action introspection (reference)
  • Action triggering (reference)
If you’re looking to expose Nango actions as tools for LLMs, check out our MCP documentation.

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Reliability and security

Nango provides infrastructure to build robust AI integrations:
  • Logs, metrics, and alerts for visibility
  • Automatic queuing and retries
  • Granular scopes and permissions
  • Selective data access (per integration and endpoint)

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How Nango uses AI

We also use AI internally to expand our integration catalog. In particular, it automates:
  • Parsing API documentation
  • Generation & review of integration code
  • Generation of integration documentation
  • Maintenance & testing of integrations