# Server-sent events (SSE)

Published articles for Server-sent events (SSE).

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## Dart Client for Genkit

DevFeed: [Dart Client for Genkit](<https://devfeed.tech/articles/dart-client-for-genkit-23886.md>)

Original publisher: [Read original article](<https://medium.com/firebase-developers/dart-client-for-genkit-call-genkit-flows-from-flutter-dart-b5a2c9b9400e?source=rss----8e8b7dc6774d---4>)

Author: Nozomi Koborinai

Published: 2025-10-23T10:49:27Z

Content type: tutorial

Language: en

Sources: [Firebase Developers - Medium](<https://devfeed.tech/sources/firebase-developers-medium.md>)

Topics: [Genkit](<https://devfeed.tech/topics/genkit.md>), [Dart](<https://devfeed.tech/topics/dart.md>), [client library](<https://devfeed.tech/topics/client-library.md>), [Flutter](<https://devfeed.tech/topics/flutter.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [Cloud Functions](<https://devfeed.tech/topics/cloud-functions.md>), [Cloud Run](<https://devfeed.tech/topics/cloud-run.md>)

Tags: [ai-development](<https://devfeed.tech/tags/ai-development.md>), [apis](<https://devfeed.tech/tags/apis.md>), [client-library](<https://devfeed.tech/tags/client-library.md>), [dart](<https://devfeed.tech/tags/dart.md>), [firebase](<https://devfeed.tech/tags/firebase.md>), [flutter](<https://devfeed.tech/tags/flutter.md>), [genkit](<https://devfeed.tech/tags/genkit.md>), [google-cloud-platform](<https://devfeed.tech/tags/google-cloud-platform.md>), [http](<https://devfeed.tech/tags/http.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [server-sent-events-sse](<https://devfeed.tech/tags/server-sent-events-sse.md>), [streaming](<https://devfeed.tech/tags/streaming.md>)

### AI overview

This article introduces a Dart client library for calling Genkit flows deployed on a server from Flutter or other Dart applications. It explains that the library handles Genkit request and response conventions, reduces repeated HTTP client code, supports authentication mechanisms, and simplifies streaming responses through Server-Sent Events. The client can call flows implemented with Genkit JS, TypeScript, or Go when their server endpoints are accessible.

### Source excerpt

Introducing the Dart Client for GenkitCalling Genkit Flows from Flutter/DartDart client for Genkit I'm a big fan of Firebase and often choose Flutter as my front-end framework. Since Google I/O 2024, I've been continuously exploring Genkit. Developed by the Firebase team, Genkit is an open-source framework from Google that simplifies the definition of AI-powered processing sequences on the server-side as Flows. Genkit | Open-source AI development framework by Google However, calling a server-defined flow from a Dart/Flutter client application required some extra effort. To bridge this gap, I developed the Dart client for Genkit package. genkit | Dart package Note: This library is not for defining Genkit flows themselves. It is specifically designed for easily and securely calling flows deployed on a server from a Dart client.Library overview As mentioned above, this library is a dedicated client for easily calling Genkit flows deployed on a server (e.g., as Web APIs on platforms like Cloud Functions for Firebase, Cloud Run, or GKE). It is not for implementing Genkit flows in Dart. The challenges before Previously, calling a Genkit flow from Dart/Flutter required manually implementing an HTTP client according to a set of conventions. For example, here's a typical piece of code using the dio package to call an image generation flow defined in Genkit. Future<String> generateImage({required String imageDescription}) async { try { final response = await dio.post( 'https://<YOUR_GENKIT_ENDPOINT>/generateImage', data: { 'data': { 'imageDescription': imageDescription, }, }, ); if (response.statusCode == 200) { return response.data['result']['url'] as String; } throw Exception('Failed to generate image: ${response.statusCode}'); } on DioException catch (e) { throw Exception('Failed to generate image: ${e.message}'); } } This code presents several challenges: When sending a request, the input must be wrapped in {'data': ...}, and when receiving a response, the result must be ex

## Supercharge your Firebase Studio workflow with MCP servers

DevFeed: [Supercharge your Firebase Studio workflow with MCP servers](<https://devfeed.tech/articles/supercharge-your-firebase-studio-workflow-with-mcp-servers-16620.md>)

Original publisher: [Read original article](<https://firebase.blog/posts/2025/07/supercharge-firebase-studio-with-mcp>)

Author: James O'Reilly

Published: 2025-07-09T00:00:00Z

Content type: tutorial

Language: en

Sources: [Firebase Blog](<https://devfeed.tech/sources/firebase-blog.md>)

Topics: [Firebase](<https://devfeed.tech/topics/firebase.md>), [Model Context Protocol (MCP)](<https://devfeed.tech/topics/model-context-protocol-mcp.md>), [MCP Server](<https://devfeed.tech/topics/mcp-server.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Development](<https://devfeed.tech/topics/development.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [configuration](<https://devfeed.tech/tags/configuration.md>), [development](<https://devfeed.tech/tags/development.md>), [environment-variables](<https://devfeed.tech/tags/environment-variables.md>), [firebase](<https://devfeed.tech/tags/firebase.md>), [firebase-studio](<https://devfeed.tech/tags/firebase-studio.md>), [gemini](<https://devfeed.tech/tags/gemini.md>), [mcp](<https://devfeed.tech/tags/mcp.md>), [mcp-server](<https://devfeed.tech/tags/mcp-server.md>), [model-context-protocol](<https://devfeed.tech/tags/model-context-protocol.md>), [server-sent-events](<https://devfeed.tech/tags/server-sent-events.md>), [server-sent-events-sse](<https://devfeed.tech/tags/server-sent-events-sse.md>), [tutorials](<https://devfeed.tech/tags/tutorials.md>)

### AI overview

This Firebase team tutorial explains how Firebase Studio integrates with Model Context Protocol servers to extend AI-assisted development with external tools and data sources. It describes MCP server configuration, supported stdio and SSE or Streamable HTTP transports, environment variables, authentication limitations, and the lack of support for GUI-dependent or desktop-session servers.

### Source excerpt

News, tutorials, and updates from the Firebase team.

## Ep. 3: Proper Prompt Formatting for Enhanced AI Model Performance

DevFeed: [Ep. 3: Proper Prompt Formatting for Enhanced AI Model Performance](<https://devfeed.tech/articles/ep-3-proper-prompt-formatting-for-enhanced-ai-model-performance-22250.md>)

Original publisher: [Read original article](<https://www.ardanlabs.com/blog/2024/07/ep3-proper-prompt-formatting-for-enhanced-ai-model-performance.html>)

Published: 2024-07-25T00:00:00Z

Content type: tutorial

Language: en

Sources: [William Kennedy](<https://devfeed.tech/sources/william-kennedy.md>)

Topics: [Generative AI](<https://devfeed.tech/topics/generative-ai.md>), [AI Models](<https://devfeed.tech/topics/ai-models.md>), [API](<https://devfeed.tech/topics/api.md>), [Streaming](<https://devfeed.tech/topics/streaming.md>), [Go Language](<https://devfeed.tech/topics/go-language.md>)

Tags: [ai-generated-responses](<https://devfeed.tech/tags/ai-generated-responses.md>), [ai-integration-techniques](<https://devfeed.tech/tags/ai-integration-techniques.md>), [ai-interaction-best-practices](<https://devfeed.tech/tags/ai-interaction-best-practices.md>), [ai-models](<https://devfeed.tech/tags/ai-models.md>), [ai-prompt-formatting](<https://devfeed.tech/tags/ai-prompt-formatting.md>), [ai-response-quality](<https://devfeed.tech/tags/ai-response-quality.md>), [api](<https://devfeed.tech/tags/api.md>), [api-convenience-for-ai](<https://devfeed.tech/tags/api-convenience-for-ai.md>), [chat-completions-endpoints](<https://devfeed.tech/tags/chat-completions-endpoints.md>), [dynamic-ai-user-experience](<https://devfeed.tech/tags/dynamic-ai-user-experience.md>), [enhancing-ai-model-performance](<https://devfeed.tech/tags/enhancing-ai-model-performance.md>), [generative-ai-series](<https://devfeed.tech/tags/generative-ai-series.md>), [go](<https://devfeed.tech/tags/go.md>), [go-programming-with-ai](<https://devfeed.tech/tags/go-programming-with-ai.md>), [optimizing-ai-prompts](<https://devfeed.tech/tags/optimizing-ai-prompts.md>), [prompt](<https://devfeed.tech/tags/prompt.md>), [proper-prompt-formatting](<https://devfeed.tech/tags/proper-prompt-formatting.md>), [real-time-ai-interactions](<https://devfeed.tech/tags/real-time-ai-interactions.md>), [server-sent-events-sse](<https://devfeed.tech/tags/server-sent-events-sse.md>), [streaming](<https://devfeed.tech/tags/streaming.md>)

### AI overview

This episode explains how structured prompt formats can improve AI model responses, how chat completion APIs simplify prompt construction, and how server-sent events enable incremental response streaming. Examples use the Hermes model and Go.

### Source excerpt

Introduction: Welcome to Episode 3 of our Intro to Generative AI series! In this episode, Daniel explores the critical aspect of prompt formatting when working with AI models, emphasizing how proper formatting can significantly enhance the quality of the AI's responses and overall performance. Prompt Formatting: Learn the importance of using specific prompt formats for AI models to enhance response quality. API Convenience: Discover how chat completions endpoints simplify prompt formatting and improve integration. Response Streaming: Understand how to handle real-time, partial completions using server-sent events (SSE) for dynamic AI interactions.