Airflow as an AI Agent’s Toolkit: Unlocking 1000+ Integrations with MCP

AI agents transform conversational prompts into actionable automation provided they have reliable access to essential tools like data warehouses, cloud storage, and APIs.

Now imagine exposing Airflow’s rich integration layer directly to AI agents via the emerging Model Context Protocol (MCP). This isn’t just gluing AI into Airflow; it’s turning Airflow into a structured execution layer for adaptive, agentic logic with full observability, retries, and audit trails built in.

We’ll demonstrate a real-world fraud detection pipeline powered by agents: suspicious transactions are analyzed, enriched dynamically with external customer data via MCP, and escalated based on validated, structured outputs. Every prompt, decision, and action is auditable and compliant.

We will then explore how Airflow can be extended into a conversational future - such as querying Snowflake from natural language, inspecting AWS S3 files, or executing BigQuery operations directly via agent prompts.

Explore the next potential evolution of Airflow - going beyond scheduling DAGs and empowering conversational AI agents with a toolkit of over 1,000 integrations you already use and trust.