OpenCode Cowork Proxy Worker

This project lets Claude use OpenCode Go models, and some OpenCode Zen models.

Claude normally speaks the Anthropic API format. OpenCode Go mostly speaks OpenAI-compatible API format. This small Cloudflare Worker sits in the middle and translates between them.

I covered how to set this up in Claude in How to Use Claude Code for Free with OpenCode.

Image / Vision Support

When you attach an image in Claude Code and send it through this proxy, the request is automatically routed to Qwen3.5 Plus (qwen3.5-plus) — a vision-capable model on OpenCode Go. This happens transparently: the proxy detects image blocks in your request, translates them to OpenAI's image format, and overrides the model to Qwen3.5 Plus so the model can actually see the image.

No configuration needed — it just works as long as you have an OpenCode Go subscription.

Set Up In Claude

If you want the fastest working setup, use minimax-m2.5-free as the first model.

Deploy this Worker to Cloudflare.
Copy your deployed Worker URL.
In Claude, open Configure third-party Inference.
Choose the gateway / third-party inference option.
Set the base URL to YOUR_DEPLOYED_WORKER_URL/zen.
Set the auth scheme to x-api-key.
Paste your OpenCode API key.
Add minimax-m2.5-free as the model name.

Important: do not add /v1/messages to the URL. Claude adds that path automatically.

Quick Claude Configuration

Use these values in Claude's Configure third-party Inference screen:

Setting	Value
Provider	Gateway / third-party inference gateway
Base URL	`YOUR_DEPLOYED_WORKER_URL/zen`
Auth scheme	`x-api-key`
API key	Your OpenCode API key
Models	Add manually, for example `minimax-m2.5-free`

For the default example above, use /zen because minimax-m2.5-free is a Zen model. Use /go for OpenCode Go models instead. Do not add /v1/messages yourself. Claude adds the API path automatically.

What This Does

The Worker accepts Claude's Anthropic-style requests at /v1/messages, converts them to OpenAI-style requests, and sends them to OpenCode Go by default.

You can choose an OpenCode upstream by adding a prefix to the Worker URL:

Worker URL suffix	Upstream
no suffix	OpenCode Go
`/go`	OpenCode Go
`/zen`	OpenCode Zen

For example, use YOUR_DEPLOYED_WORKER_URL/go for Go models and YOUR_DEPLOYED_WORKER_URL/zen for Zen models.

It also handles tool calls, streaming, and DeepSeek reasoning output so coding-agent workflows work correctly.

Important: this proxy has been live-tested with minimax-m2.7. Other OpenCode Go models are included from the public OpenCode Go model list, but provider behavior can vary, especially around streaming usage/token accounting.

Important Zen Limitation

OpenCode Zen support is partial.

This proxy currently works with Zen models that use the OpenAI-compatible /chat/completions endpoint.

Known Zen model categories that should work through /zen:

Zen model category	Examples
OpenAI-compatible chat models	`qwen3.6-plus`, `qwen3.5-plus`, `minimax-m2.7`, `minimax-m2.5`, `minimax-m2.5-free`, `glm-5.1`, `glm-5`, `kimi-k2.5`, `kimi-k2.6`, `big-pickle`, `ling-2.6-flash`, `hy3-preview-free`, `nemotron-3-super-free`

Known Zen model categories that do not work yet through this proxy:

Zen model category	Why it does not work yet
GPT models such as `gpt-5.5`	Zen exposes these through `/responses`, and this proxy does not yet translate Anthropic Messages to OpenAI Responses API.
Claude models such as `claude-sonnet-4-6`	Zen exposes these through `/messages`; this proxy's `/zen` Claude path currently translates to OpenAI-compatible `/chat/completions`.
Gemini models such as `gemini-3.1-pro`	Zen exposes these through model-specific endpoints, not the generic chat-completions path used here.

Use /go for OpenCode Go. Use /zen only for Zen models listed as OpenAI-compatible chat models in the OpenCode Zen endpoint docs.

For Developers (OpenCode Cowork Proxy Worker)

Technically, this is a Cloudflare Worker gateway that lets Anthropic/Claude clients talk to OpenAI-compatible APIs, and lets OpenAI clients talk to Anthropic-compatible APIs.

The default upstream is OpenCode Go:

https://opencode.ai/zen/go/v1

This means Claude can be configured to use OpenCode Go models through this proxy without additional server-side configuration.

Claude / Anthropic SDK  ->  /v1/messages           ->  OpenAI-compatible upstream
OpenAI SDK              ->  /v1/chat/completions   ->  OpenAI-compatible upstream
OpenAI SDK              ->  /v1/chat/completions   ->  Anthropic upstream with x-upstream-format: anthropic

Detailed Claude Setup

Use Claude's Configure third-party Inference flow and add the Worker as a custom gateway.

Configure the gateway like this:

Setting	Value
Base URL	Your deployed Worker URL, or add `/go` or `/zen`
Auth scheme	`x-api-key`
API key	Your OpenCode Go API key
Model	Add manually, for example `deepseek-v4-pro`

Do not include /v1/messages in the Claude base URL. Claude will call /v1/messages; the Worker handles that path.

Use /go for OpenCode Go subscription models. Use /zen only for OpenCode Zen models available through the OpenAI-compatible /chat/completions endpoint. Zen GPT /responses, Zen Claude /messages, and Zen Gemini model-specific endpoints are not supported yet.

Manual Model Setup

Claude may not discover the OpenCode Go models automatically. Add the model manually in Configure third-party Inference.

Common OpenCode Go model IDs:

Model	Model ID	Upstream API style
GLM-5.1	`glm-5.1`	OpenAI-compatible
GLM-5	`glm-5`	OpenAI-compatible
Kimi K2.5	`kimi-k2.5`	OpenAI-compatible
Kimi K2.6	`kimi-k2.6`	OpenAI-compatible
DeepSeek V4 Pro	`deepseek-v4-pro`	OpenAI-compatible
DeepSeek V4 Flash	`deepseek-v4-flash`	OpenAI-compatible
MiMo-V2-Pro	`mimo-v2-pro`	OpenAI-compatible
MiMo-V2-Omni	`mimo-v2-omni`	OpenAI-compatible
MiMo-V2.5-Pro	`mimo-v2.5-pro`	OpenAI-compatible
MiMo-V2.5	`mimo-v2.5`	OpenAI-compatible
MiniMax M2.7	`minimax-m2.7`	Anthropic-compatible upstream
MiniMax M2.5	`minimax-m2.5`	Anthropic-compatible upstream
Qwen3.6 Plus	`qwen3.6-plus`	OpenAI-compatible
Qwen3.5 Plus	`qwen3.5-plus`	OpenAI-compatible

For the latest list, see the OpenCode Go endpoint docs:

https://opencode.ai/docs/go/#endpoints

For OpenCode's own config files, model IDs use the opencode-go/<model-id> format. For Claude's third-party inference setup through this proxy, use the raw API model ID such as deepseek-v4-pro, kimi-k2.6, or qwen3.5-plus.

`claude.json` Example

You can also configure Claude with a claude.json gateway entry. Replace the Worker URL and API key with your own values.

{
  "inferenceProvider": "gateway",
  "inferenceGatewayBaseUrl": "YOUR_DEPLOYED_WORKER_URL/go",
  "inferenceGatewayApiKey": "YOUR_OPENCODE_GO_API_KEY",
  "inferenceGatewayAuthScheme": "x-api-key",
  "inferenceModels": [
    {
      "name": "glm-5.1"
    },
    {
      "name": "glm-5"
    },
    {
      "name": "kimi-k2.5"
    },
    {
      "name": "kimi-k2.6"
    },
    {
      "name": "deepseek-v4-pro"
    },
    {
      "name": "deepseek-v4-flash"
    },
    {
      "name": "mimo-v2-pro"
    },
    {
      "name": "mimo-v2-omni"
    },
    {
      "name": "mimo-v2.5-pro"
    },
    {
      "name": "mimo-v2.5"
    },
    {
      "name": "minimax-m2.7"
    },
    {
      "name": "minimax-m2.5"
    },
    {
      "name": "qwen3.6-plus"
    },
    {
      "name": "qwen3.5-plus"
    }
  ]
}

Deploy On Cloudflare

This project is intended to run as a Cloudflare Worker. Deploy it to Cloudflare using either the deploy button above or Cloudflare's Git-based Worker deployment flow.

Use these settings when connecting the repository in Cloudflare:

Setting	Value
Build command	empty
Deploy command	`npm run deploy`
Production branch	`main`

Do not deploy this as a normal Node.js web app. wrangler deploy builds and publishes the Worker from wrangler.toml.

Configuration

The Worker is zero-config by default. It forwards to OpenCode Go using OpenAI-compatible format. You can also route to OpenCode Zen by adding /zen to the Worker URL.

Optional request headers:

Header	Default	Description
`x-upstream-url`	`https://opencode.ai/zen/go/v1`	Upstream API base URL
`x-upstream-format`	`openai`	Upstream format: `openai` or `anthropic`
`x-api-key`	required	Upstream API key
`authorization`	optional	`Bearer <key>` also works
`anthropic-version`	`2023-06-01`	Forwarded when calling Anthropic-compatible upstreams
`anthropic-beta`	unset	Forwarded when calling Anthropic-compatible upstreams

The API key is validated locally before any upstream call. Missing or short keys receive a 401 response.

Prefix routes:

Path prefix	Upstream base URL
`/go`	`https://opencode.ai/zen/go/v1`
`/zen`	`https://opencode.ai/zen/v1`

API Endpoints

Path	Method	Purpose
`/v1/messages`	POST	Anthropic Messages API. Translates to OpenAI format by default.
`/v1/chat/completions`	POST	OpenAI Chat Completions API. Pass-through by default.
`/v1/models`	GET	Model discovery proxy.

OpenAI SDK Usage

Point any OpenAI-compatible client at the gateway. By default, /v1/chat/completions passes through to OpenCode Go.

from openai import OpenAI

client = OpenAI(
    base_url="YOUR_DEPLOYED_WORKER_URL/v1",
    api_key="your-opencode-go-api-key",
)

response = client.chat.completions.create(
    model="deepseek-v4-pro",
    messages=[{"role": "user", "content": "Hello"}],
)

OpenAI SDK To Anthropic

Set x-upstream-format: anthropic and point x-upstream-url at an Anthropic-compatible API.

curl YOUR_DEPLOYED_WORKER_URL/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_ANTHROPIC_KEY" \
  -H "x-upstream-url: https://api.anthropic.com" \
  -H "x-upstream-format: anthropic" \
  -d '{"model":"claude-sonnet-4-20250514","messages":[{"role":"user","content":"Hello"}]}'

Translation Notes

The gateway handles:

Anthropic Messages requests to OpenAI Chat Completions requests
OpenAI Chat Completions responses to Anthropic Messages responses
Tool calls and tool results in both directions
Streaming SSE in both directions
DeepSeek/OpenAI reasoning_content as Anthropic thinking blocks
Prompt cache key injection for OpenAI-style prefix caching

Prompt Caching

When translating Anthropic to OpenAI, the gateway injects a prompt_cache_key derived from a hash of the system prompt. This keeps requests with the same system prompt routed to the same backend node when the upstream supports OpenAI-style prefix caching.

Cache hit tokens from OpenAI-compatible usage metadata are mapped back to Anthropic's cache_read_input_tokens field.

Development

npm install
npm test
npm run deploy -- --dry-run

Project structure:

src/
├── index.ts                          Main Worker router and auth gate
├── auth.ts                           API key extraction and validation
├── cache.ts                          Prompt cache key utilities
└── translate/
    ├── request/                      Request translators
    ├── response/                     Response translators
    └── stream/                       SSE stream translators
test/
├── auth.test.ts
├── cache.test.ts
├── index.test.ts
├── request.test.ts
├── response.test.ts
└── stream.test.ts

License

MIT. See LICENSE.

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
src		src
test		test
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
package-lock.json		package-lock.json
package.json		package.json
tsconfig.json		tsconfig.json
vitest.config.ts		vitest.config.ts
wrangler.toml		wrangler.toml

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OpenCode Cowork Proxy Worker

Image / Vision Support

Set Up In Claude

Quick Claude Configuration

What This Does

Important Zen Limitation

For Developers (OpenCode Cowork Proxy Worker)

Detailed Claude Setup

Manual Model Setup

`claude.json` Example

Deploy On Cloudflare

Configuration

API Endpoints

OpenAI SDK Usage

OpenAI SDK To Anthropic

Translation Notes

Prompt Caching

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OpenCode Cowork Proxy Worker

Image / Vision Support

Set Up In Claude

Quick Claude Configuration

What This Does

Important Zen Limitation

For Developers (OpenCode Cowork Proxy Worker)

Detailed Claude Setup

Manual Model Setup

claude.json Example

Deploy On Cloudflare

Configuration

API Endpoints

OpenAI SDK Usage

OpenAI SDK To Anthropic

Translation Notes

Prompt Caching

Development

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