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open-responses-server

Wraps any OpenAI API interface as Responses with MCPs support so it supports Codex. Adding any missing stateful features. Ollama and Vllm compliant.

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Description

Wraps any OpenAI API interface as Responses with MCPs support so it supports Codex. Adding any missing stateful features. Ollama and Vllm compliant.

README

🚀 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.

✨ 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.

🔥 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

🏗️ Quick Install

Latest release on PyPI:

pip install open-responses-server

Or install from source:

pip install uv
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

Docker images are available for linux/amd64, linux/arm64, and linux/arm/v7 architectures. Works great with docker-compose.yaml for Codex + your own model.

🛠️ Configure

Minimal config to connect your AI backend:

OPENAI_BASE_URL_INTERNAL=http://localhost:8000   # Your LLM backend (Ollama typically on :11434, vLLM on :8000)
OPENAI_BASE_URL=http://localhost:8080            # This server's endpoint
OPENAI_API_KEY=sk-mockapikey123456789            # Mock key tunneled to backend
MCP_SERVERS_CONFIG_PATH=./mcps.json              # Path to mcps servers json file 

Server binding:

API_ADAPTER_HOST=0.0.0.0
API_ADAPTER_PORT=8080

Streaming and connection:

STREAM_TIMEOUT=120.0                # HTTP timeout (seconds) for streaming requests
HEARTBEAT_INTERVAL=15.0             # SSE keepalive interval (seconds)

Conversation and tool handling:

MAX_CONVERSATION_HISTORY=100        # Max stored conversation entries
MAX_TOOL_CALL_ITERATIONS=25         # Max tool-call loop iterations
MCP_TOOL_REFRESH_INTERVAL=10        # Seconds between MCP tool cache refreshes

Logging:

LOG_LEVEL=INFO                      # DEBUG, INFO, WARNING, ERROR, CRITICAL
LOG_FILE_PATH=./log/api_adapter.log # Path to log file

Configure with CLI tool:

# Interactive configuration setup
otc configure

Verify setup:

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

💬 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

Star History Chart

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

📚 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:

Naming history

This repo had changed names:

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

Release History

VersionChangesUrgencyDate
v0.4.3## What's Changed * new version 0.4.1 by @OriNachum in https://github.com/teabranch/open-responses-server/pull/45 * docs: refresh architecture, event system docs, Jekyll cream theme, and skills by @OriNachum in https://github.com/teabranch/open-responses-server/pull/46 * fix: support streamable-http and SSE MCP transports by @OriNachum in https://github.com/teabranch/open-responses-server/pull/47 * test: improve test coverage from 22% to 91% by @OriNachum in https://github.com/teabranch/open-resMedium3/30/2026
v0.4.1Both **Chat Completions** and **Responses API** endpoints both now **support MCP**. Known issue: Codex around Responses API doesn't present MCP result correctly, but can be seen by the user.Low6/22/2025
v0.3.4Release v0.3.4Low5/20/2025
v0.3.3Release v0.3.3Low5/19/2025
v0.3.2Release v0.3.2Low5/16/2025
v0.3.1Release v0.3.1Low5/14/2025
v0.2.7removing openai from package nameLow5/14/2025
v0.2.6Tested on Nvidia Jetson with OllamaLow5/9/2025
v0.2.5Tested on Nvidia Jetson with OllamaLow5/9/2025
v0.2.4Release v0.2.4Low5/9/2025
v0.2.2See resources/example-simple-request.png Command works. The request goes through the proxy to Groq. This lets us add support for Web research (crawl4ai), file search (Graphiti) and more. MCPs planned as well.Low5/3/2025
v0.1.13Release v0.1.13Low5/3/2025
v0.1.12Release v0.1.12Low5/3/2025
v0.1.11Release v0.1.11Low5/3/2025
v0.1.6Release v0.1.6Low4/25/2025
v0.1.5Release v0.1.5Low4/25/2025
v0.1.3Release v0.1.3Low4/25/2025
v0.1.1Release v0.1.1Low4/25/2025
v0.1.0Release v0.1.0Low4/25/2025

Dependencies & License Audit

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