# **TIBCO Flogo® Demos**

End-to-end proof-of-concept demonstrations showcasing **TIBCO Flogo®** as a **low-code iPaaS** for **AI-powered services**, **MCP server integration**, **GraphQL APIs**, and **real-time machine learning inference** — ready to clone, run, and explore.

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## Index

| Demo | Category | Description |
|------|----------|-------------|
| [AI-Powered Customer Service](./ai-powered-customer-service/) | AI & MCP | MCP server integrating CRM, order management, and notifications for AI agents (Claude Desktop, Cursor, VS Code) |
| [AI-Powered MFT](./flogo-mcp-mft/) | AI & MCP | MCP server for TIBCO Managed File Transfer — AI-powered B2B file transfer, user management, and audit trails |
| [GraphQL](./flogo-graphql/) | Integration | GraphQL trigger with MongoDB resolvers for device data queries, with Docker Compose deployment |
| [ML Anomaly Detection](./flogo-machine-learning-anomaly-detection/) | AI & ML | Real-time temperature anomaly detection using Python scikit-learn Isolation Forest, deployable to TIBCO Platform |

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## Prerequisites

All demos require:
- **Microsoft Visual Studio Code** with the **TIBCO Flogo® Extension** installed
- **TIBCO Flogo® 2.26.x** or later

Additional requirements per demo:

| Demo | Additional Prerequisites |
|------|------------------------|
| AI-Powered Customer Service | Node.js v16+, Go v1.19+, MCP-compatible AI client |
| AI-Powered MFT | TIBCO MFT environment, Claude Desktop, Docker Desktop |
| GraphQL | Docker, Docker Compose, MongoDB |
| ML Anomaly Detection | Python 3.x with scikit-learn, numpy, fastapi |

See each demo's `README.md` for detailed setup and run instructions.

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## Feedback

Please contact us at [integration-pm@tibco.com](mailto:integration-pm@tibco.com) with any queries, feedback, or comments.

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**Topics:** `AI Agents` · `MCP Server` · `GraphQL` · `Machine Learning` · `Low-Code` · `iPaaS`
