OpenAI + Python AI Stack
Build AI applications with OpenAI and Python
Full bundle for LLM-powered application development. Conforms strictly to the official OpenAI OpenAPI spec. Includes OpenAI MCP config, Python cursor rules, and a hosted edge endpoint. Build agents, RAG systems, and chat applications with AI-assisted coding.
MCP Config URL
Auto-updating hosted config
https://mcpbridge.org/config/openai.jsonUse this URL in your MCP client config under mcpServers.
Hosted Endpoint
Live MCP server, always available
mcpbridge.org/mcp/openaiNo local setup needed. Works with any MCP client out of the box.
📂 Starter Template File Tree
The exact template workspace structure included with this stack.
📁openai-python-starter
📄.cursorrules
📁.mdc
📄openai-agents.mdc
📄structured-outputs.mdc
📁app
📄main.py
📄agents.py
📄config.py
📁tests
📄test_agents.py
📄requirements.txt
📄pyproject.toml
What's Included
- Hosted Hono Edge MCP Endpoint with sub-10ms routing latency
- Auto-Syncing OpenAI OpenAPI v3 Specification (api.openai.com)
- Modular Python + FastAPI .mdc Cursor Rules Suite
- Production-ready OpenAI Python Boilerplate Codebase
- AI Prompt Kit for Assistants, RAG & Streaming API
- CLI Health Connection & Key Diagnostic Script
Highlights
- Saves 4+ hours of LLM integration setup ($360+ dev value)
- Zero egress-cost edge hosting with auto-syncing API specs
- Auto-generated structured output rules to save token costs
- Local client-side parsing ensuring zero API key leaks
Stack .cursorrules Preview
Pre-configured Cursor AI rules for building with this stack.
You are an expert AI application developer specializing in OpenAI integration with Python. # OpenAI API Use the latest OpenAI Python SDK. Implement retry logic with exponential backoff for rate limits (429). Use structured output parsing for reliable JSON responses. Handle token limits with proper truncation and chunking. Implement streaming for real-time responses. Cache frequent completions with functools.lru_cache. Use environment variables for API keys. Log token usage for cost tracking. Implement proper error handling for APIErrors and Timeouts. # Python Write type-annotated code (Python 3.12+). Follow PEP 8. Use src/ layout for packages. Use async/await for I/O. Use generators for large datasets. Implement proper error handling. Use pytest with async support for testing. # FastAPI Use Pydantic models for request/response validation. Use async endpoints. Implement dependency injection with Depends. Use proper exception handlers. Document with automatic OpenAPI schema.
Start for $4.50
Get hosted endpoint, auto-updating specs, rules suite & boilerplates.
First month just $4.50 (50% discount auto-applied)Cancel anytime • 30-day money-back guarantee
Save $4.50 on your first month