What is Open Responses Server

open-responses-server is a plug-and-play server that interfaces with OpenAI’s Responses API, allowing compatibility with various AI backends such as Ollama, vLLM, and OpenAI itself. It supports stateful features and is designed for running OpenAI’s Codex and other API clients against custom models.

Use cases

Use cases include running OpenAI’s Coding Assistant (Codex) with self-hosted models, experimenting with LLMs while preserving API compatibility, and developing innovative AI solutions in research and enterprise environments.

How to use

To use open-responses-server, install it via pip with ‘pip install open-responses-server’ or from source. Start the server using the CLI tool with ‘otc start’ or directly from the source. For Docker deployment, run the provided Docker command with necessary environment variables.

Key features

Key features include compatibility with OpenAI’s Responses API, support for various AI backends, stateful chat handling, tool call support, and future enhancements like file search and code interpretation. It is designed to be scalable, reliable, and secure for enterprise use.

Where to use

open-responses-server can be used in various fields such as software development, AI research, and any application requiring interaction with AI models while maintaining OpenAI API compatibility.

🚀 open-responses-server

A plug-and-play server that speaks OpenAI’s Responses API—no matter which AI backend you’re running.

Ollama? vLLM? LiteLLM? Even OpenAI itself?
This server bridges them all to the OpenAI ChatCompletions & Responses API interface.

In plain words:
👉 Want to run OpenAI’s Coding Assistant (Codex) or other OpenAI API clients against your own models?
👉 Want to experiment with self-hosted LLMs but keep OpenAI’s API compatibility?

This project makes it happen.
It handles stateful chat, tool calls, and future features like file search & code interpreter—all behind a familiar OpenAI API.

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✨ Why use this?

✅ Acts as a drop-in replacement for OpenAI’s Responses API.
✅ Lets you run any backend AI (Ollama, vLLM, Groq, etc.) with OpenAI-compatible clients.
✅ MCP support around both Chat Completions and Responses APIs
✅ Supports OpenAI’s new Coding Assistant / Codex that requires Responses API.
✅ Built for innovators, researchers, OSS enthusiasts.
✅ Enterprise-ready: scalable, reliable, and secure for production workloads.

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🔥 What’s in & what’s next?

✅ Done 📝 Coming soon

• ✅ Tool call support .env file support
• ✅ Manual & pipeline tests
• ✅ Docker image build
• ✅ PyPI release
• 📝 Persistent state (not just in-memory)
• ✅ CLI validation
• 📝 hosted tools:
  • ✅ MCPs support
  • 📝 Web search: crawl4ai
  • 📝 File upload + search: graphiti
  • 📝 Code interpreter
  • 📝 Computer use APIs

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🏗️ Quick Install

Latest release on PyPI:

pip install open-responses-server

Or install from source:

uv venv
uv pip install .
uv pip install -e ".[dev]"  # dev dependencies

Run the server:

# Using CLI tool (after installation)
otc start

# Or directly from source
uv run src/open_responses_server/cli.py start

Docker deployment:

# Run with Docker
docker run -p 8080:8080 \
  -e OPENAI_BASE_URL_INTERNAL=http://your-llm-api:8000 \
  -e OPENAI_BASE_URL=http://localhost:8080 \
  -e OPENAI_API_KEY=your-api-key \
  ghcr.io/teabranch/open-responses-server:latest

Works great with docker-compose.yaml for Codex + your own model.

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🛠️ Configure

Minimal config to connect your AI backend:

OPENAI_BASE_URL_INTERNAL=http://localhost:11434  # Ollama, vLLM, Groq, etc.
OPENAI_BASE_URL=http://localhost:8080            # This server's endpoint
OPENAI_API_KEY=sk-mockapikey123456789            # Mock key tunneled to backend

Server binding:

API_ADAPTER_HOST=0.0.0.0
API_ADAPTER_PORT=8080

Optional logging:

LOG_LEVEL=INFO
LOG_FILE_PATH=./log/api_adapter.log

Configure with CLI tool:

# Interactive configuration setup
otc configure

Verify setup:

# Check if the server is working
curl http://localhost:8080/v1/models

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💬 We’d love your support!

If you think this is cool:
⭐ Star the repo.
🐛 Open an issue if something’s broken.
🤝 Suggest a feature or submit a pull request!

This is early-stage but already usable in real-world demos.
Let’s build something powerful—together.

Star History

Projects using this middleware

• Agentic Developer MCP Server - a wrapper around Codex, transforming Codex into an agentic developer node over a folder. Together with this (ORS) repo, it becomes a link in a tree/chain of developers.
• Nvidia jetson devices - docker compose with ollama

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📚 Citations & inspirations

Referenced projects

• SearXNG MCP
• UncleCode. (2024). Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper [Computer software]. GitHub. Crawl4AI repo

Cite this project

Code citation

@software{open-responses-server,
  author = {TeaBranch},
  title = {open-responses-server: Open-source server bridging any AI provider to OpenAI’s Responses API},
  year = {2025},
  publisher = {GitHub},
  journal = {GitHub Repository},
  howpublished = {\url{https://github.com/teabranch/open-responses-server}},
  commit = {use the commit hash you’re working with}
}

Text citation

TeaBranch. (2025). open-responses-server: Open-source server the serves any AI provider with OpenAI ChatCompletions as OpenAI’s Responses API and hosted tools. [Computer software]. GitHub. https://github.com/teabranch/open-responses-server

Links:

• Python library
• GitHub repository
• GitHub Pages

Naming history

This repo had changed names:

• openai-responses-server (Changed to avoid brand name OpenAI)
• open-responses-server