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Claude Code Router

I am seeking funding support for this project to better sustain its development. If you have any ideas, feel free to reach out to me: m@musiiot.top

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A powerful tool to route Claude Code requests to different models and customize any request.

✨ Features

  • 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.

🚀 Getting Started

1. Installation

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

2. Configuration

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 to true. When set to false, no log files will be created. Default is true.

  • LOG_LEVEL (optional): Set the logging level. Available options are: "fatal", "error", "warn", "info", "debug", "trace". Default is "debug".

  • Logging Systems: The Claude Code Router uses two separate logging systems:

    • Server-level logs: HTTP requests, API calls, and server events are logged using pino in the ~/.claude-code-router/logs/ directory with filenames like ccr-*.log
    • Application-level logs: Routing decisions and business logic events are logged in ~/.claude-code-router/claude-code-router.log
  • APIKEY (optional): You can set a secret key to authenticate requests. When set, clients must provide this key in the Authorization header (e.g., Bearer your-secret-key) or the x-api-key header. Example: "APIKEY": "your-secret-key".

  • HOST (optional): You can set the host address for the server. If APIKEY is not set, the host will be forced to 127.0.0.1 for security reasons to prevent unauthorized access. Example: "HOST": "0.0.0.0".

  • NON_INTERACTIVE_MODE (optional): When set to true, enables compatibility with non-interactive environments like GitHub Actions, Docker containers, or other CI/CD systems. This sets appropriate environment variables (CI=true, FORCE_COLOR=0, etc.) and configures stdin handling to prevent the process from hanging in automated environments. Example: "NON_INTERACTIVE_MODE": true.

  • 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.

Environment Variable Interpolation

Claude Code Router supports environment variable interpolation for secure API key management. You can reference environment variables in your config.json using either $VAR_NAME or ${VAR_NAME} syntax:

{
  "OPENAI_API_KEY": "$OPENAI_API_KEY",
  "GEMINI_API_KEY": "${GEMINI_API_KEY}",
  "Providers": [
    {
      "name": "openai",
      "api_base_url": "https://api.openai.com/v1/chat/completions",
      "api_key": "$OPENAI_API_KEY",
      "models": ["gpt-5", "gpt-5-mini"]
    }
  ]
}

This allows you to keep sensitive API keys in environment variables instead of hardcoding them in configuration files. The interpolation works recursively through nested objects and arrays.

Here is a comprehensive example:

{
  "APIKEY": "your-secret-key",
  "PROXY_URL": "http://127.0.0.1:7890",
  "LOG": true,
  "API_TIMEOUT_MS": 600000,
  "NON_INTERACTIVE_MODE": false,
  "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"
  }
}

3. Running Claude Code with the Router

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

4. UI Mode

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.

UI

Providers

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

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 the openrouter 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 additional tooluse transformer is applied only to the deepseek-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 the Anthropic 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 a provider 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 specific max_tokens value.
  • tooluse: Optimizes tool usage for certain models via tool_choice.
  • gemini-cli (experimental): Unofficial support for Gemini via Gemini CLI gemini-cli.js.
  • reasoning: Used to process the reasoning_content field.
  • sampling: Used to process sampling information fields such as temperature, top_p, top_k, and repetition_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 the cache_control field from requests.
  • vertex-gemini: Handles the Gemini API using Vertex authentication.
  • qwen-cli (experimental): Unofficial support for qwen3-coder-plus model via Qwen CLI qwen-cli.js.
  • rovo-cli (experimental): Unofficial support for gpt-5 via Atlassian Rovo Dev CLI rovo-cli.js.

Custom Transformers:

You can also create your own transformers and load them via the transformers field in config.json.

{
  "transformers": [
    {
      "path": "/User/xxx/.claude-code-router/plugins/gemini-cli.js",
      "options": {
        "project": "xxx"
      }
    }
  ]
}

Router

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

Custom Router

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": "/User/xxx/.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:

// /User/xxx/.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;
};
Subagent Routing

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...

Status Line (Beta)

To better monitor the status of claude-code-router at runtime, version v1.0.40 includes a built-in statusline tool, which you can enable in the UI. statusline-config.png

The effect is as follows: statusline

🤖 GitHub Actions

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' > $HOME/.claude-code-router/config.json
          {
            "log": true,
            "NON_INTERACTIVE_MODE": true,
            "OPENAI_API_KEY": "${{ 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"

Note: When running in GitHub Actions or other automation environments, make sure to set "NON_INTERACTIVE_MODE": true in your configuration to prevent the process from hanging due to stdin handling issues.

This setup allows for interesting automations, like running tasks during off-peak hours to reduce API costs.

📝 Further Reading

❤️ Support & Sponsoring

If you find this project helpful, please consider sponsoring its development. Your support is greatly appreciated!

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A huge thank you to all our sponsors for their generous support!

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Use Claude Code as the foundation for coding infrastructure, allowing you to decide how to interact with the model while enjoying updates from Anthropic.

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