BenedictKing/ccx
ccx
Claude / Codex / Gemini API Proxy - CCX
Usage guide
ccx is an open-source project around claude, codex, gemini with 2,634 GitHub stars. This guide focuses on when to use it, how to install it, how to run the first example, and what to verify before adopting it.
Key features
- Implemented mainly in Go, useful for judging integration effort in a similar stack.
- GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
- The project has a homepage, so cross-check docs, examples, and release information beyond GitHub.
Best for
- Evaluating ccx for Go AI workflows.
- Comparing a GitHub project with 2,634 stars and current repository activity.
Pros
- ccx has visible GitHub traction with 2,634 stars. Topics: claude, codex, gemini.
- The project provides an external homepage for deeper evaluation.
Cons
- Production fit still depends on documentation depth, issue activity, and release cadence.
- License review should confirm the MIT terms fit your use case.
Production readiness
ccx should be validated with its README, release history, open issues, and integration requirements before production use.
License risk
MIT is reported by GitHub; review the repository license before redistribution or commercial use.
ccx architecture preview
ccx's main path starts at the entry surface, runs through Coding agent runtime, combines OpenAI / Claude / Gemini, Repository context, GitHub / APIs / webhooks, and returns Code changes / developer feedback.
Entry
Web / product entry
Users start from a web UI, hosted product surface, or browser-based workflow.
https://benedictking.github.io/ccx/
Runtime
Coding agent runtime
The runtime reads developer intent, inspects repository context, plans edits, and returns code-oriented actions.
coding workflow
Model
OpenAI / Claude / Gemini
Model calls are likely routed through OpenAI, Claude, Gemini based on README and topic signals.
OpenAI, Claude, Gemini
Context
Repository context
Runtime state, user input, repository files, or configuration provide context for each task.
context signal
Tools
GitHub / APIs / webhooks
Tool adapters let the runtime act outside the model through GitHub / APIs / webhooks.
GitHub, APIs / webhooks
Output
Code changes / developer feedback
The final result is code edits, explanations, repository actions, or developer-facing feedback.
coding output
Install tutorial
Before you install
- Docker Engine with enough disk space for images and volumes
- Local build tools for compiling the project
- A clean working directory for the first test run
Check the runtime environment
ccx has Docker in the setup path. Confirm Docker Engine works and reserve enough disk space for images and volumes.
Get the project files
Start from the official repository or package so the first run matches the documented behavior.
$ git clone https://github.com/BenedictKing/ccx.gitInstall or build dependencies
Run the next setup command detected from the project documentation.
$ docker run -d \Adoption guidance and sources
Practical use cases
Claude / Codex / Gemini API Proxy - CCX
This is one of the documented reasons to evaluate ccx before choosing a stack.
Focus area: claude
This is one of the documented reasons to evaluate ccx before choosing a stack.
AI Coding project comparison
Compare ccx with similar projects before committing to a stack.
Before adopting
- Complete one clean-environment verification using the official ccx setup path.
- Review repository license, model weights, external services, and dependency terms for your use case.
- Check recent commits, release cadence, issue response, and documentation depth.
- Evaluate output quality, latency, resource usage, and recovery behavior with a small dataset.
Configuration notes
- Check exposed ports, mounted volumes, and environment variables before running the container in a shared environment.
Sources checked
These links are used to verify repository, documentation, or tutorial details. Review the source pages before adopting the project.
Troubleshooting
- If Docker startup fails, check port conflicts, image pull permissions, and volume paths first.
- If installation fails, first confirm the command is being run from the README-specified directory.
- If dependencies conflict, retry in a fresh virtual environment, container, or working directory.
- If output looks wrong, return to the smallest documented ccx example before adding complex data.
- For keys, model files, or external services, verify environment variables, local paths, and permissions one by one.
What is ccx?
ccx is an open-source ai coding project. Claude / Codex / Gemini API Proxy - CCX
How do I install ccx?
Start with the official README. The first detected setup step is: git clone https://github.com/BenedictKing/ccx.git.
Is ccx beginner-friendly?
If you already know the Go ecosystem, start with the smallest example. Otherwise test it in an isolated environment first.
Can ccx be used commercially?
GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
Does ccx need a GPU?
GPU requirements depend on the workload, model, and dataset size. Start with the smallest README example before scaling up.
How should I decide whether to adopt ccx?
Evaluate setup cost, maintenance activity, issue health, license terms, and fit with your real workflow.