Favro users have built and published open-source MCP (Model Context Protocol) servers that allow you to connect Favro to AI tools like Claude Code, Cursor, and others.
With an MCP server, you can interact with your Favro data through natural language. Create cards, update boards, pull status reports, and more, directly from your AI assistant.
Where to find them
Example 1:
Community made and maintained Favro MCP servers are available on GitHub:
Each repo includes setup instructions. Follow the README to get connected.
Example 2:
Pipedream, a Workday company, is hosting their own Favro MCP server here:
Important: use at your own risk
These servers are built and maintained by the community, not by Favro. We have not reviewed, tested, or vetted them for security, reliability, or accuracy.
By using a community-built MCP server, you accept that:
Favro is not responsible for any issues, data loss, or unintended changes caused by third-party servers.
You should review the source code and understand what permissions you're granting before connecting any tool to your Favro organization.
Support for these servers is handled by their respective maintainers, not by Favro's support team.
In short: these are community projects. We think it's great that they exist, but you use them at your own risk.
Our recommended approach for working with agents: build skills backed by the Favro API instead of using MCP servers
If you want the most control and reliability when connecting AI agents to Favro, we recommend building skills backed by scripts that use the Favro API directly, instead of using an MCP server. This gives you full control over what data is read and written, access to more of Favro's feature set, no dependency on third-party code you don't control, and typically better context management and token efficiency by fetching only the data needed for each task.
Learn more here: Favro API documentation
A relevant example: Meeting to Favro in seconds
One of our team members created this workflow: feeding a meeting transcript to an AI agent and having it create or add to existing Favro cards. Action items, owners, context, all structured and ready to go in the right place.
Working with agents in Favro is easier than you think. Teams are already doing this in ways we didn't expect. Here's a prompt example to get your imagination going:
"Build a skill that turns my transcripts from meetings into Favro cards or card updates using api + scripts.
The skill should break the transcript down into key learnings and action points. Then it should prompt me to answer if I want to add it to an existing card (ask for card link) or if it should create a new card (ask for board link). I'm using [insert notetaking software]. Let me know what additional information you need from me to build this."
Here is a short video showing this in action with the Favro CRM solution.
Watch here (4 min):
This is just one way to use agents with Favro. We are confident this example will inspire you to many more.