npm package: @swarmcode/swarm-router
Description: Swarm Router - Advanced Model Routing and Configuration for Claude Code
Author: rinadelph
Latest version: 1.0.52

![](blog/images/swarm-router-img.png)

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

![](blog/images/claude-code.png)

## ✨ 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.
- **MITM Command Interception**: Intercept and route Claude Code local commands (like `/compact`) to specific models.

## 🧪 Experimental Features & Known Issues

This router works amazingly well for advanced model routing, but there are some current limitations and workarounds:

### Known Issues & Workarounds

**Thinking Mode (`think` command)**
- ✅ **Works**: Thinking routing is functional and routes to designated thinking models
- ⚠️ **Issue**: Doesn't work with Claude Code's native thinking mode enabled
- 🔧 **Workaround**: When using the `think` command, turn off Claude Code's thinking mode with `/t` to disable reasoning headers. This allows seamless routing to your configured thinking model.

**Compact Mode (`/compact` command)**
- ✅ **Works**: Compact routing works amazingly for conversation summarization
- ⚠️ **Issue**: Timing issue where requests are sent before the new client is initialized
- 🔧 **Workaround**: After using `/compact`, press `Esc Esc` and navigate back to the compact response to see the results

### Recommended Workflow

For optimal performance, consider using a larger context model (like GPT-5 Mini with 400k context) as your main orchestrator, with smaller ephemeral models for specific tasks:

- **Main Model**: Large context model (GPT-5, Claude Opus) for primary conversations
- **Quick Tasks**: Fast models (Claude Sonnet) for rapid responses
- **Syntax/Grep**: Ultra-fast models (Cerebras Qwen 3) for immediate syntax fixes and code analysis
- **Compacting**: Set to trigger at ~150k conversation context for better context management

This approach leverages the strengths of each model type while maintaining conversation continuity through the larger context orchestrator.

## 🚀 Getting Started

### 1. Installation

First, ensure you have [Claude Code](https://docs.anthropic.com/en/docs/claude-code/quickstart) installed:

```shell
npm install -g @anthropic-ai/claude-code
```

Then, install Swarm Router:

```shell
npm install -g @swarmcode/swarm-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 Swarm 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

Swarm 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:

```json
{
  "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:

```json
{
  "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:

```shell
ccr code
```

> **Note**: After modifying the configuration file, you need to restart the service for the changes to take effect:
>
> ```shell
> ccr restart
> ```

### 4. UI Mode

For a more intuitive experience, you can use the UI mode to manage your configuration:

```shell
ccr ui
```

This will open a web-based interface where you can easily view and edit your `config.json` file.

![UI](/blog/images/ui.png)

#### 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.
  ```json
  {
    "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.

  ```json
  {
    "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.
  ```json
  {
    "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](https://openrouter.ai/docs/features/provider-routing). See an example below:
  ```json
    "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](https://gist.github.com/musistudio/1c13a65f35916a7ab690649d3df8d1cd).
- `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.
- `chutes-glm` Unofficial support for GLM 4.5 model via Chutes [chutes-glm-transformer.js](https://gist.github.com/vitobotta/2be3f33722e05e8d4f9d2b0138b8c863).
- `qwen-cli` (experimental): Unofficial support for qwen3-coder-plus model via Qwen CLI [qwen-cli.js](https://gist.github.com/musistudio/f5a67841ced39912fd99e42200d5ca8b).
- `rovo-cli` (experimental): Unofficial support for gpt-5 via Atlassian Rovo Dev CLI [rovo-cli.js](https://gist.github.com/SaseQ/c2a20a38b11276537ec5332d1f7a5e53).

**Custom Transformers:**

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

```json
{
  "transformers": [
    {
      "path": "/User/xxx/.swarm-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.
- `image` (beta): Used for handling image-related tasks (supported by CCR's built-in agent). If the model does not support tool calling, you need to set the `config.forceUseImageAgent` property to `true`.
- `compact`: Used for routing `/compact` commands from Claude Code. The router intercepts these commands and routes them to the specified model for efficient conversation summarization.

- 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`

#### MITM Command Interception

Swarm Router can intercept and route Claude Code's local commands (like `/compact`) to specific models. This feature acts as a Man-in-the-Middle (MITM) system to:

1. **Intercept Commands**: Detects Claude Code local commands before they reach the default provider
2. **Route to Specific Models**: Routes intercepted commands to configured models
3. **Transform Messages**: Automatically transforms the command into an appropriate format for the target model
4. **Log Activity**: Creates audit logs for all intercepted commands

**Configuration Example:**

```json
{
  "Router": {
    "default": "deepseek,deepseek-chat",
    "background": "ollama,qwen2.5-coder:latest",
    "compact": "openai,gpt-5-nano"  // Routes /compact commands
  }
}
```

**How it Works:**

When you use `/compact` in Claude Code:
1. CCR intercepts the command before it reaches the API
2. The command is routed to the model specified in `Router.compact`
3. The request is transformed into a summarization task
4. The response is returned to Claude Code as if it came from the original API

**Supported Commands:**
- `/compact`: Conversation summarization (routes to `Router.compact`)

**Note:** If you're using models that require `max_completion_tokens` instead of `max_tokens` (like `gpt-5-nano`), make sure to configure the appropriate transformer:

```json
{
  "transformer": {
    "gpt-5-nano": {
      "use": ["maxcompletiontokens"]
    }
  }
}
```

#### 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`:

```json
{
  "CUSTOM_ROUTER_PATH": "/User/xxx/.swarm-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`:

```javascript
// /User/xxx/.swarm-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 Swarm Router at runtime, version v1.0.40 includes a built-in statusline tool, which you can enable in the UI.
![statusline-config.png](/blog/images/statusline-config.png)

The effect is as follows:
![statusline](/blog/images/statusline.png)

## 🤖 GitHub Actions

Integrate Swarm Router into your CI/CD pipeline. After setting up [Claude Code Actions](https://docs.anthropic.com/en/docs/claude-code/github-actions), modify your `.github/workflows/claude.yaml` to use the router:

```yaml
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/.swarm-code-router
          cat << 'EOF' > $HOME/.swarm-code-router/config.json
          {
            "log": true,
            "NON_INTERACTIVE_MODE": true,
            "OPENAI_API_KEY": "${{ secrets.OPENAI_API_KEY }}",
            "OPENAI_BASE_URL": "https://api.deepseek.com",
            "OPENAI_MODEL": "deepseek-chat"
          }
          EOF
        shell: bash

      - name: Start Swarm Router
        run: |
          nohup ~/.bun/bin/bunx @musistudio/swarm-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.