 | TIBCO Flogo® (formerly known as TIBCO Flogo® Enterprise) enables AI orchestration and intelligent automation through a visual flow designer integrated into Visual Studio Code. Built on a high-performance Go (Golang) engine, it delivers superior runtime efficiency, an ultra-light memory footprint, fast startup, and low-latency processing across edge, cloud, serverless, and on-premises environments. With its AI-ready architecture and powerful set of connectors, Flogo® transforms enterprise data into intelligent, event-driven, AI-ready workflows. To understand all the capabilities, see Build Event-driven Apps with an Ultralight Framework. |
| Read the documentation |
What's new in version 2.26.4 (May 2026)
Flow Instance ID now included in Error Object: The flowInstanceId is now included in the data of the Error object, supporting error correlation with specific flow instances.
TIBCO Flogo® Connector for Google Cloud Storage: TIBCO Flogo® Connector for Google Cloud Storage now supports the List Activity. For more information, see Google Cloud Storage List.
TIBCO Flogo® Connector for Agentic AI - Tech Preview:
Support for agents to communicate with each other using the A2A protocol has been added.
The new LLM Client activity allows you to dynamically configure the LLM provider, model, and authentication at runtime, eliminating the need for pre-configured connections.
A new input field, filteredToolNames, has been added to the AI Agent activity. It accepts a string array to limit the tools available during an invocation and enable context reduction.
For complete release details, see TIBCO Flogo® 2.26.4 Release Notes.
When working with TIBCO Flogo®, you may find the following videos useful:
Introducing TIBCO FLOGO Model Context Protocol (MCP) Connector
Installing TIBCO Flogo Extension for VS Code and Creating first Flogo App
Creation of Unit Testing & Play Test Case in Flogo
Create your first REST API
Flogo Quick Start 2.21.0
Deploy to AWS Lambda
Subflows
Build App Binary
Adding Flogo Extensions via Github URL
Application metrics
Turning your Flogo app into a
GraphQL Server implementation
App configuration with environment variables
CI/CD + Devops demo
When creating Flogo apps, you can import and customize any of the predefined samples. These samples demonstrate how to develop, test, and deploy a Flogo app using various capabilities. In the Flogo GitHub repository for samples, each sample is organized by category and contains a Readme file. Perform the instructions in the Readme file to import the sample to your workspace and use it. The following samples are currently available:
Includes REST, graphQL, and gRPC samples
Includes sample to integrate your data (customers, products, sales) with AI Agents using TIBCO Flogo® MCP Connector (Developer Preview) for natural language querying.
Includes Flogo connector samples for DB Connectors, Messaging, and more
Includes samples to create unit tests, assertions, and mocking for activities
Includes sample for deploying a Flogo app as an Azure function
Includes sample for deploying a Flogo app using custom app image
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