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shuremali02
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chatkit-python

Build a FastAPI chat backend with SSE streaming and SQLModel persistence.

Updated Dec 28, 2025
Search Tags:#fastapi#mcp#gemini#sse#openai-agents#chatkit#conversation-persistence
One-click install
npx skills add https://github.com/shuremali02/The-Evolution-of-Todo---Mastering-Spec-Driven-Development---Cloud-Native-AI --skill chatkit-python-shuremali02
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: chatkit-python
Source: https://github.com/shuremali02/The-Evolution-of-Todo---Mastering-Spec-Driven-Development---Cloud-Native-AI/tree/main/.claude/skills/chatkit-python
Command: npx skills add https://github.com/shuremali02/The-Evolution-of-Todo---Mastering-Spec-Driven-Development---Cloud-Native-AI --skill chatkit-python-shuremali02

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Build custom chat API backends for OpenAI ChatKit frontend using FastAPI, providing SSE streaming, conversation persistence, and MCP/Gemini integration.

Core Features & Use Cases

  • SSE streaming chat endpoint via FastAPI for real-time conversations
  • Conversation persistence using SQLModel for histories and thread management
  • MCP tool integration to perform task workflows (add_task, list_tasks, complete_task, delete_task)
  • Fallback behavior when MCP server is unavailable
  • Optional authentication integration pattern for secure endpoints
  • Non-streaming chat endpoint for simple integrations

Quick Start

Deploy the FastAPI chat backend and point your ChatKit frontend to the /api/chat endpoint to begin streaming assistant responses.

Frequently Asked Questions about chatkit-python

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a FastAPI chat backend with SSE streaming?▼

FastAPI chat backends with SSE streaming provide real-time conversation updates to ChatKit frontends via a /api/chat endpoint, persisting chat histories using SQLModel and integrating MCP tools for task workflows.

How does conversation persistence work in a FastAPI chat application?▼

Conversation persistence in a FastAPI chat backend uses SQLModel to store chat histories and manage thread sessions, ensuring multi-user chat contexts maintain state across multiple interactions.

Can I integrate MCP tools with a FastAPI SSE streaming endpoint?▼

Yes, you can integrate MCP tools with a FastAPI SSE streaming endpoint to execute task workflows like add_task, list_tasks, complete_task, and delete_task, including fallback handling when the MCP server is unavailable.

Does the ChatKit FastAPI backend support non-streaming chat endpoints?▼

Yes, the ChatKit FastAPI backend supports a non-streaming chat endpoint for simple integrations alongside the primary SSE streaming endpoint, offering flexibility depending on your frontend architecture requirements.

What happens when the MCP server is unavailable in a FastAPI chat backend?▼

When the MCP server is unavailable, the FastAPI chat backend implements fallback behavior to ensure the SSE streaming chat endpoint remains operational without interrupting the core conversation experience.

Do I need OpenAI agents to use the FastAPI chat backend with ChatKit?▼

The FastAPI chat backend integrates with ChatKit frontends and supports OpenAI agents alongside Gemini integration, requiring you to point your frontend to the /api/chat endpoint to begin streaming responses.

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