Seems like a promising area to invest in given the benefits it can provide to the users as mentioned by Shahar and Abhishek.
Abhishek also has a promising talk submitted which i am looking forward to this year at the summit. In any case, this seems to be one of the first of the very few implementations of trying to integrate Airflow officially / unofficially with an MCP server. Thanks & Regards, Amogh Desai On Thu, May 29, 2025 at 2:56 AM Aaron Dantley <aarondant...@gmail.com> wrote: > Hey! > > I also think this is a great idea! > > Would it be possible to be included in the development process? > > Sorry I’m new to this group, but would appreciate any suggestions on how to > contribute to the MCP server development! > > Regards! > Aaron > > On Wed, May 28, 2025 at 2:57 PM Avi <a...@astronomer.io.invalid> wrote: > > > Nice to see the idea to incorporate an official MCP server for > > Airflow. It's been really magical to see what a simple LLM can do with an > > Airflow MCP server built just from APIs. > > > > A few things that I noticed in my experience: > > - The number of tools that the OpenAPI spec generates is quite huge. Most > > tools (*Claude, VS Code with GitHub Copilot, Cursor, Windsurf*) which > uses > > mcp-client limits it to a number of 100 tools. (*The read-only mode > creates > > less tools in comparison*.) > > - MCP server are just not tools. There are other things as well, like > > resources and prompts. Prompts are super helpful in case of debugging for > > example. It is a way of teaching LLM about Airflow. Say I want to have a > > failing task investigated. A prompt can be helpful in letting LLM know a > > step-by-step process of carrying out the investigation. > > - Where do you run the MCP server? I wouldn't want my laptop to do the > > heavy processing, which would want us to go for the SSE instead of stdio. > > > > This is why I chose two different path of using mcp server with airflow, > > which I intend to talk about at the summit. > > > > 1. AI-Augmented Airflow - This helped me add a chat interface inside > > Airflow using a plugin to talk to an Airflow instance (read only mode). > > > > 2. Airflow-Powered AI - Experimenting with this has been totally magical, > > how powerful AI can become when it has access to airflow. Also, a > directory > > structure to maintain the DAGs, and it can write DAGs on the fly. I > totally > > see a need where LLMs eventually will need a scheduler, although a > complete > > airflow just for an LLM might seem a bit overkill to the rest of the > > community. > > > > I chose to build this on top of open API is because that was the only way > > to get proper RBAC enabled. > > > > I have so many points to discuss. Would love to hear from the community > and > > then take it forward. > > > > Thanks, > > Avi > > > > > > > > On Wed, May 28, 2025 at 6:32 PM Aritra Basu <aritrabasu1...@gmail.com> > > wrote: > > > > > I definitely think there's potential to interact with an airflow MCP > > > server. Though I think I'd be interested to see how many and how > > frequently > > > people are making use of MCP servers in the wild before investing > effort > > in > > > building and maintaining one for airflow. I'm sure the data is > available > > > out there, just needs finding. > > > -- > > > Regards, > > > Aritra Basu > > > > > > On Wed, 28 May 2025, 11:18 pm Julian LaNeve, > > <jul...@astronomer.io.invalid > > > > > > > wrote: > > > > > > > I think this would be interesting now that the Streamable HTTP spec < > > > > > > > > > > https://modelcontextprotocol.io/specification/2025-03-26/basic/transports> > > > > is out. I think in theory we could publish this first as an Airflow > > > > provider that installs a plugin to expose an MCP endpoint, as a PoC - > > > this > > > > becomes a much nicer experience than a local stdio one. > > > > -- > > > > Julian LaNeve > > > > CTO > > > > > > > > Email: jul...@astronomer.io > > > > <mailto:jul...@astronomer.io>Mobile: 330 509 5792 > > > > > > > > > On May 28, 2025, at 1:25 PM, Shahar Epstein <sha...@apache.org> > > wrote: > > > > > > > > > > Dear community, > > > > > > > > > > Following the thread on Slack [1], initiated by Jason Sebastian > > Kusuma, > > > > I'd > > > > > like to start an effort to officially support MCP in Airflow's > > > codebase. > > > > > > > > > > *Some background * > > > > > Model Context Protocol (MCP) is an open standard, open-source > > framework > > > > > that standardizes the way AI models like LLM integrate and share > data > > > > with > > > > > external tools, systems and data sources. Think of it as a "USB-C > for > > > > AI" - > > > > > a universal connector that simplifies and standardizes AI > > > integrations. A > > > > > notable example of an MCP server is GitHub's official > implementation > > > > [3], which > > > > > allows LLMs such as Claude, Copilot, and OpenAI (or: "MCP clients") > > to > > > > > fetch pull request details, analyze code changes, and generate > review > > > > > summaries. > > > > > > > > > > *How could an MCP server be useful in Airflow?* > > > > > Imagine the possibilities when LLMs can seamlessly interact with > > > > Airflow’s > > > > > API: triggering DAGs using natural language, retrieving DAG run > > > history, > > > > > enabling smart debugging, and more. This kind of integration opens > > the > > > > door > > > > > to a more intuitive, conversational interface for workflow > > > orchestration. > > > > > > > > > > *Why do we need to support it officially?* > > > > > Quid pro quo - LLMs become an integral part of the modern > development > > > > > experience, while Airflow evolves into the go-to for orchestrating > AI > > > > > workflows. By officially supporting it, we’ll enable multiple users > > to > > > > > interact with Airflow through their LLMs, streamlining automation > and > > > > > improving accessibility across diverse workflows. All of that is > > viable > > > > > with relatively small development effort (see next paragraph). > > > > > > > > > > *How should it be implemented?* > > > > > As of today, there have been several implementations of MCP servers > > for > > > > > Airflow API, the most visible one [4] made by Abhishek Bhakat from > > > > > Astronomer. > > > > > The efforts of implementing it and maintaining it in our codebase > > > > shouldn't > > > > > be too cumbersome (at least in theory), as we could utilize > packages > > > like > > > > > fastmcp to auto-generate the server using the existing OpenAPI > specs. > > > I'd > > > > > be very happy if Abhishek could share his experience in this > thread. > > > > > > > > > > *Where else could we utilize MCP?* > > > > > Beyond the scope of the public API, I could also imagine using it > to > > > > > communicate with Breeze. > > > > > > > > > > *How do we proceed from here?* > > > > > Feel free to share your thoughts here in this discussion. > > > > > If there are no objections, I'll be happy to start working on an > AIP. > > > > > > > > > > > > > > > Sincerely, > > > > > Shahar Epstein > > > > > > > > > > > > > > > *References:* > > > > > [1] Slack discussion, > > > > > > > > > https://apache-airflow.slack.com/archives/C06K9Q5G2UA/p1746121916951569 > > > > > [2] Introducing the model context protocol, > > > > > https://www.anthropic.com/news/model-context-protocol > > > > > [3] GitHub Official MCP server, > > > > https://github.com/github/github-mcp-server > > > > > [4] Unofficial MCP Server made by Abhishek Hakat, > > > > > https://github.com/abhishekbhakat/airflow-mcp-server > > > > > > > > > > > > > >
