# Integrating YepCode with crewAI: Build Multi-Agent AI Workflows That Run Real Code Date review: Jun 10, 2025 --- Modern AI agents can do more than just chat—they can reason, collaborate, and even execute real code to solve complex tasks. > **What if you could combine multi-agent intelligence with cloud-powered code execution?** In this post, you’ll see how to connect [crewAI](https://crewai.com/) and [YepCode](/content/site-root.html) to build a workflow where agents not only think, but act—automating a real-world scenario from start to finish. ### Motivation & Use Case Why multi-agent systems? Because real-world problems are rarely solved by a single expert—they require collaboration, specialization, and the ability to take action. > Imagine automating scientific analysis and reporting, end-to-end, with agents that both think and do. In this demo, we tackle a scenario with real stakes: assessing the impact of an asteroid hitting Earth. (Okay, it’s a fun and slightly tongue-in-cheek example—but perfect for showing how agents can combine reasoning, data, and automation to deliver results you can use.) _No planets were harmed in the making of this post._ ### Tech Stack Overview This project brings together two powerful tools: - **crewAI**: Lets you build teams of AI agents that can reason, collaborate, and delegate tasks—just like a real crew. - **YepCode**: A cloud platform where agents can run real code, automate workflows, and interact with APIs on the fly. > **Together, they let your agents not only think, but act.** ### Scenario: Asteroid Impact Assessment Our agents are on a mission: figure out what would happen if an asteroid hit Earth, and write up a dramatic report. - **Asteroid Data Scientist**: Crunches the numbers and calculates the impact. - **Impact Reporter**: Turns the data into a story that’s fun (and maybe a little scary) to read. #### Project Setup Getting started is easy: 1. [**Clone the repo**](https://github.com/yepcode/crewai-yepcode-demo) and create a virtual environment. 2. **Install dependencies** with a couple of commands. 3. **Copy `.env.example` to `.env`** and add your API keys. > You’ll need Python 3.10–3.12, plus a free YepCode and OpenAI account. #### Defining Agents and Tasks Agents and their goals are defined in simple YAML files: - `agents.yaml`: Who does what (e.g., Data Scientist, Reporter) - `tasks.yaml`: What needs to be done, and in what order > Tweak these files to create your own agent teams and workflows! #### Integrating YepCode For this scenario, we’re using the [YepCode MCP server](https://github.com/yepcode/mcp-server-js)—an ideal fit when agents need to run real code and automate complex tasks. While CrewAI lets you [create custom tools](https://docs.crewai.com/concepts/tools) directly in your project, using YepCode MCP is even more powerful: - You can define, update, and manage your tools in YepCode’s platform. - Instantly expose new tools to your agents with just a line of code—no redeploy needed. - Perfect for scientific tasks, data processing, or any workflow where flexibility and cloud execution matter. In this project, the **Asteroid Data Scientist** agent uses YepCode MCP to perform calculations. By default, YepCode MCP provides a `run_code` action that can execute any Python or JavaScript code—so your agent can dynamically generate and run code to solve the problem, not just call a fixed API. > You can also create your own custom tools in YepCode—like a dedicated “Calculate Asteroid Impact Energy” process. (I’ll show how to add and use a custom tool in [this post](/content/blog/yepcode-mcp-user-defined-tools-ai-automation/index.html), with the code and setup!) This flexibility is what makes YepCode MCP a perfect match for agent-based workflows. ### Running the Workflow Just run one command: You will be prompted with all the crewAI workflow steps in the terminal, showing how agents collaborate to solve the task. _Steps taken by the crew_ Once the workflow ends you’ll get a file like `asteroid_impact_report.md` with the outcome. _Preview of asteroid_impact_report.md file_ ### Conclusion By combining crewAI and YepCode, you unlock a new level of AI automation—where agents can collaborate, reason, and execute real code to solve real problems. [GitHub Repository](https://github.com/yepcode/crewai-yepcode-demo) > Try the repo, remix the agents, and imagine what you could automate next! Curious to try this for your own API or use case? [Contact us](/content/contact/index.html) — we’d love to hear what you’re building.