- Model Routing: Route requests to different models based on your needs (e.g., background tasks, thinking, long context).
- Multi-Provider Support: Supports various model providers like OpenRouter, DeepSeek, Ollama, Gemini, Volcengine, and SiliconFlow.
- Request/Response Transformation: Customize requests and responses for different providers using transformers.
- Dynamic Model Switching: Switch models on-the-fly within Claude Code using the
/model
command. - GitHub Actions Integration: Trigger Claude Code tasks in your GitHub workflows.
- Plugin System: Extend functionality with custom transformers.
First, ensure you have Claude Code installed:
npm install -g @anthropic-ai/claude-code
Then, install Claude Code Router:
npm install -g @musistudio/claude-code-router
Create and configure your ~/.claude-code-router/config.json
file. For more details, you can refer to config.example.json
.
The config.json
file has several key sections:
PROXY_URL
(optional): You can set a proxy for API requests, for example:"PROXY_URL": "http://127.0.0.1:7890"
.LOG
(optional): You can enable logging by setting it totrue
. The log file will be located at$HOME/.claude-code-router.log
.APIKEY
(optional): You can set a secret key to authenticate requests. When set, clients must provide this key in theAuthorization
header (e.g.,Bearer your-secret-key
) or thex-api-key
header. Example:"APIKEY": "your-secret-key"
.HOST
(optional): You can set the host address for the server. IfAPIKEY
is not set, the host will be forced to127.0.0.1
for security reasons to prevent unauthorized access. Example:"HOST": "0.0.0.0"
.Providers
: Used to configure different model providers.Router
: Used to set up routing rules.default
specifies the default model, which will be used for all requests if no other route is configured.API_TIMEOUT_MS
: Specifies the timeout for API calls in milliseconds.
Here is a comprehensive example:
{
"APIKEY": "your-secret-key",
"PROXY_URL": "http://127.0.0.1:7890",
"LOG": true,
"API_TIMEOUT_MS": 600000,
"Providers": [
{
"name": "openrouter",
"api_base_url": "https://openrouter.ai/api/v1/chat/completions",
"api_key": "sk-xxx",
"models": [
"google/gemini-2.5-pro-preview",
"anthropic/claude-sonnet-4",
"anthropic/claude-3.5-sonnet",
"anthropic/claude-3.7-sonnet:thinking"
],
"transformer": {
"use": ["openrouter"]
}
},
{
"name": "deepseek",
"api_base_url": "https://api.deepseek.com/chat/completions",
"api_key": "sk-xxx",
"models": ["deepseek-chat", "deepseek-reasoner"],
"transformer": {
"use": ["deepseek"],
"deepseek-chat": {
"use": ["tooluse"]
}
}
},
{
"name": "ollama",
"api_base_url": "http://localhost:11434/v1/chat/completions",
"api_key": "ollama",
"models": ["qwen2.5-coder:latest"]
},
{
"name": "gemini",
"api_base_url": "https://generativelanguage.googleapis.com/v1beta/models/",
"api_key": "sk-xxx",
"models": ["gemini-2.5-flash", "gemini-2.5-pro"],
"transformer": {
"use": ["gemini"]
}
},
{
"name": "volcengine",
"api_base_url": "https://ark.cn-beijing.volces.com/api/v3/chat/completions",
"api_key": "sk-xxx",
"models": ["deepseek-v3-250324", "deepseek-r1-250528"],
"transformer": {
"use": ["deepseek"]
}
},
{
"name": "modelscope",
"api_base_url": "https://api-inference.modelscope.cn/v1/chat/completions",
"api_key": "",
"models": ["Qwen/Qwen3-Coder-480B-A35B-Instruct", "Qwen/Qwen3-235B-A22B-Thinking-2507"],
"transformer": {
"use": [
[
"maxtoken",
{
"max_tokens": 65536
}
],
"enhancetool"
],
"Qwen/Qwen3-235B-A22B-Thinking-2507": {
"use": ["reasoning"]
}
}
},
{
"name": "dashscope",
"api_base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions",
"api_key": "",
"models": ["qwen3-coder-plus"],
"transformer": {
"use": [
[
"maxtoken",
{
"max_tokens": 65536
}
],
"enhancetool"
]
}
},
{
"name": "aihubmix",
"api_base_url": "https://aihubmix.com/v1/chat/completions",
"api_key": "sk-",
"models": [
"Z/glm-4.5",
"claude-opus-4-20250514",
"gemini-2.5-pro"
]
}
],
"Router": {
"default": "deepseek,deepseek-chat",
"background": "ollama,qwen2.5-coder:latest",
"think": "deepseek,deepseek-reasoner",
"longContext": "openrouter,google/gemini-2.5-pro-preview",
"longContextThreshold": 60000,
"webSearch": "gemini,gemini-2.5-flash"
}
}
Start Claude Code using the router:
ccr code
Note: After modifying the configuration file, you need to restart the service for the changes to take effect:
ccr restart
For a more intuitive experience, you can use the UI mode to manage your configuration:
ccr ui
This will open a web-based interface where you can easily view and edit your config.json
file.
Note: The UI mode is currently in beta. 100% vibe coding: including project initialization, I just created a folder and a project.md document, and all code was generated by ccr + qwen3-coder + gemini(webSearch). If you encounter any issues, please submit an issue on GitHub.
The Providers
array is where you define the different model providers you want to use. Each provider object requires:
name
: A unique name for the provider.api_base_url
: The full API endpoint for chat completions.api_key
: Your API key for the provider.models
: A list of model names available from this provider.transformer
(optional): Specifies transformers to process requests and responses.
Transformers allow you to modify the request and response payloads to ensure compatibility with different provider APIs.
Global Transformer: Apply a transformer to all models from a provider. In this example, the
openrouter
transformer is applied to all models under theopenrouter
provider.{ "name": "openrouter", "api_base_url": "https://openrouter.ai/api/v1/chat/completions", "api_key": "sk-xxx", "models": [ "google/gemini-2.5-pro-preview", "anthropic/claude-sonnet-4", "anthropic/claude-3.5-sonnet" ], "transformer": { "use": ["openrouter"] } }
Model-Specific Transformer: Apply a transformer to a specific model. In this example, the
deepseek
transformer is applied to all models, and an additionaltooluse
transformer is applied only to thedeepseek-chat
model.{ "name": "deepseek", "api_base_url": "https://api.deepseek.com/chat/completions", "api_key": "sk-xxx", "models": ["deepseek-chat", "deepseek-reasoner"], "transformer": { "use": ["deepseek"], "deepseek-chat": { "use": ["tooluse"] } } }
Passing Options to a Transformer: Some transformers, like
maxtoken
, accept options. To pass options, use a nested array where the first element is the transformer name and the second is an options object.{ "name": "siliconflow", "api_base_url": "https://api.siliconflow.cn/v1/chat/completions", "api_key": "sk-xxx", "models": ["moonshotai/Kimi-K2-Instruct"], "transformer": { "use": [ [ "maxtoken", { "max_tokens": 16384 } ] ] } }
Available Built-in Transformers:
Anthropic
:If you use only theAnthropic
transformer, it will preserve the original request and response parameters(you can use it to connect directly to an Anthropic endpoint).deepseek
: Adapts requests/responses for DeepSeek API.gemini
: Adapts requests/responses for Gemini API.openrouter
: Adapts requests/responses for OpenRouter API. It can also accept aprovider
routing parameter to specify which underlying providers OpenRouter should use. For more details, refer to the OpenRouter documentation. See an example below:"transformer": { "use": ["openrouter"], "moonshotai/kimi-k2": { "use": [ [ "openrouter", { "provider": { "only": ["moonshotai/fp8"] } } ] ] } }
groq
: Adapts requests/responses for groq API.maxtoken
: Sets a specificmax_tokens
value.tooluse
: Optimizes tool usage for certain models viatool_choice
.gemini-cli
(experimental): Unofficial support for Gemini via Gemini CLI gemini-cli.js.reasoning
: Used to process thereasoning_content
field.sampling
: Used to process sampling information fields such astemperature
,top_p
,top_k
, andrepetition_penalty
.enhancetool
: Adds a layer of error tolerance to the tool call parameters returned by the LLM (this will cause the tool call information to no longer be streamed).cleancache
: Clears thecache_control
field from requests.vertex-gemini
: Handles the Gemini API using Vertex authentication.
Custom Transformers:
You can also create your own transformers and load them via the transformers
field in config.json
.
{
"transformers": [
{
"path": "$HOME/.claude-code-router/plugins/gemini-cli.js",
"options": {
"project": "xxx"
}
}
]
}
The Router
object defines which model to use for different scenarios:
default
: The default model for general tasks.background
: A model for background tasks. This can be a smaller, local model to save costs.think
: A model for reasoning-heavy tasks, like Plan Mode.longContext
: A model for handling long contexts (e.g., > 60K tokens).longContextThreshold
(optional): The token count threshold for triggering the long context model. Defaults to 60000 if not specified.webSearch
: Used for handling web search tasks and this requires the model itself to support the feature. If you're using openrouter, you need to add the:online
suffix after the model name.
You can also switch models dynamically in Claude Code with the /model
command: /model provider_name,model_name
Example: /model openrouter,anthropic/claude-3.5-sonnet
For more advanced routing logic, you can specify a custom router script via the CUSTOM_ROUTER_PATH
in your config.json
. This allows you to implement complex routing rules beyond the default scenarios.
In your config.json
:
{
"CUSTOM_ROUTER_PATH": "$HOME/.claude-code-router/custom-router.js"
}
The custom router file must be a JavaScript module that exports an async
function. This function receives the request object and the config object as arguments and should return the provider and model name as a string (e.g., "provider_name,model_name"
), or null
to fall back to the default router.
Here is an example of a custom-router.js
based on custom-router.example.js
:
// $HOME/.claude-code-router/custom-router.js
/**
* A custom router function to determine which model to use based on the request.
*
* @param {object} req - The request object from Claude Code, containing the request body.
* @param {object} config - The application's config object.
* @returns {Promise<string|null>} - A promise that resolves to the "provider,model_name" string, or null to use the default router.
*/
module.exports = async function router(req, config) {
const userMessage = req.body.messages.find((m) => m.role === "user")?.content;
if (userMessage && userMessage.includes("explain this code")) {
// Use a powerful model for code explanation
return "openrouter,anthropic/claude-3.5-sonnet";
}
// Fallback to the default router configuration
return null;
};
For routing within subagents, you must specify a particular provider and model by including <CCR-SUBAGENT-MODEL>provider,model</CCR-SUBAGENT-MODEL>
at the beginning of the subagent's prompt. This allows you to direct specific subagent tasks to designated models.
Example:
<CCR-SUBAGENT-MODEL>openrouter,anthropic/claude-3.5-sonnet</CCR-SUBAGENT-MODEL>
Please help me analyze this code snippet for potential optimizations...
Integrate Claude Code Router into your CI/CD pipeline. After setting up Claude Code Actions, modify your .github/workflows/claude.yaml
to use the router:
name: Claude Code
on:
issue_comment:
types: [created]
# ... other triggers
jobs:
claude:
if: |
(github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
# ... other conditions
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
issues: read
id-token: write
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Prepare Environment
run: |
curl -fsSL https://bun.sh/install | bash
mkdir -p $HOME/.claude-code-router
cat << 'EOF' > $HOME/.claude-code-router/config.json
{
"log": true,
"OPENAI_API_KEY": "${{ secrets.OPENAI_API_KEY }}",
"OPENAI_BASE_URL": "https://api.deepseek.com",
"OPENAI_MODEL": "deepseek-chat"
}
EOF
shell: bash
- name: Start Claude Code Router
run: |
nohup ~/.bun/bin/bunx @musistudio/claude-code-router@1.0.8 start &
shell: bash
- name: Run Claude Code
id: claude
uses: anthropics/claude-code-action@beta
env:
ANTHROPIC_BASE_URL: http://localhost:3456
with:
anthropic_api_key: "any-string-is-ok"
This setup allows for interesting automations, like running tasks during off-peak hours to reduce API costs.
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