[OpenClaw] Practical Guide to Channel Plugin Development
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[OpenClaw] Practical Guide to Channel Plugin Development

Ethan Carter

By Ethan Carter

From Zero to One: Develop Your First OpenClaw Message Channel Plugin

GitHub: github.com/chungeplus/yeizi-openclaw-plugin

Overview

What Is OpenClaw?

OpenClaw is an open-source AI agent framework that supports extending message channels through plugins. Developers can write Channel Plugins to integrate with various messaging platforms (such as Feishu, WeChat, Slack, etc.), enabling the AI agent to receive and reply to messages.

What a Channel Plugin Does

A Channel Plugin is an extension module of OpenClaw responsible for:

  • Establishing connections with external messaging platforms
  • Receiving user messages
  • Passing messages to OpenClaw for AI processing
  • Sending AI replies back to users
┌─────────────┐      ┌─────────────┐      ┌─────────────┐
│   User      │ ───► │  Channel    │ ───► │  OpenClaw   │
│ (Feishu/    │      │   Plugin    │      │     AI      │
│  WeChat)    │      │             │      │             │
└─────────────┘      └─────────────┘      └─────────────┘
     ▲                                          │
     │                                          ▼
     └──────────────────────────────────────────┘
                    (AI Reply)

Plugin Types

OpenClaw supports multiple plugin types:

TypeDescription
Channel PluginIntegrates with messaging platforms and receives/sends messages
Skill PluginExtends AI skills
Tool PluginAdds AI tools

This guide mainly explains the development of Channel Plugins.



System Architecture

Overall Architecture Diagram

┌────────────────────────────────────────────────────────────────┐
│                         User Browser                           │
├────────────────────────────────────────────────────────────────┤
│  ┌──────────────────────────────────────────────────────────┐  │
│  │                 Web Frontend (Chat Page)                │  │
│  │  • User inputs messages                                 │  │
│  │  • Displays AI replies                                  │  │
│  │  • Real-time WebSocket communication                    │  │
│  │  • Plugin configuration display                         │  │
│  └──────────────────────────────────────────────────────────┘  │
└────────────────────────────────────────────────────────────────┘
           ▲                                    │
           │                                    │ WebSocket
      AI Reply                                  │ User Message
           │                                    ▼
           └────────────────────────────────────────────────►
                                 │
                                 ▼
┌────────────────────────────────────────────────────────────────┐
│                        Web Backend Service                     │
├────────────────────────────────────────────────────────────────┤
│  • Authentication service (AppKey + AppSecret)               │
│  • WebSocket service                                          │
│  • Message routing                                            │
│  • Configuration query API (/api/config)                     │
└────────────────────────────────────────────────────────────────┘
           ▲                                    │
           │                                    │ WebSocket
      AI Reply                                  │ Message Forwarding
           │                                    ▼
           └────────────────────────────────────────────────►
                                 │
                                 ▼
┌────────────────────────────────────────────────────────────────┐
│                         OpenClaw Plugin                        │
├────────────────────────────────────────────────────────────────┤
│  • WebSocket client (receives/sends messages)                │
│  • dispatchReplyWithBufferedBlockDispatcher                  │
│  • ChannelDock configuration                                  │
│  • YeiziDock defines plugin capabilities                      │
└────────────────────────────────────────────────────────────────┘
                                 │
                            AI Reply
                         (OpenClaw API)

Message Flow

Message Sending Flow (User → OpenClaw)

  1. The user enters a message
  2. The frontend sends the message to the backend through WebSocket
  3. The backend forwards the message to the OpenClaw plugin
  4. The plugin constructs ctxPayload
  5. It calls finalizeInboundContext
  6. It calls dispatchReplyWithBufferedBlockDispatcher to trigger AI processing

Message Reply Flow (OpenClaw → User)

  1. OpenClaw AI processing completes
  2. The deliver callback of dispatchReplyWithBufferedBlockDispatcher is triggered
  3. The plugin sends the reply to the backend through WebSocket
  4. The backend pushes it to the frontend through WebSocket
  5. The frontend displays the AI reply


Core Concepts

Channel

A Channel in OpenClaw represents a specific message source or destination. Each Channel Plugin implements one Channel.

ChannelDock

ChannelDock defines a Channel’s capabilities and metadata:

export const yeiziDock: ChannelDock = {
    id: "yeizi",
    capabilities: {
        chatTypes: ["direct"],      // Supports private chat
        blockStreaming: true,       // Supports streaming responses
    },
};

ChannelPlugin

ChannelPlugin is the core implementation of the plugin and includes:

  • meta: plugin metadata (name, description, documentation link)
  • capabilities: capability configuration (supported chat types, media support, etc.)
  • config: account management configuration
  • security: security policy
  • status: status management
  • outbound: outbound message handling
  • gateway: gateway configuration (starting accounts, handling messages)

Runtime

Runtime is the runtime environment provided by OpenClaw. The plugin interacts with the OpenClaw core through Runtime:

import { getRuntime } from './runtime';

const runtime = getRuntime();

// Use runtime for message processing
runtime.channel.reply.dispatchReplyWithBufferedBlockDispatcher({...});

Account

One Channel can be configured with multiple accounts, and each account represents an independent connection:

interface ResolvedAccount {
    accountId: string;      // Account ID
    enabled: boolean;       // Whether enabled
    configured: boolean;    // Whether configured
    name?: string;          // Account name
    config: AccountConfig;  // Account configuration
}


Development Environment Setup

Requirements

  • Node.js: >= 18.0.0
  • npm or pnpm
  • OpenClaw: >= 2026.3.12
  • Code editor (VS Code recommended)

Create a Plugin Project

# Create the project directory
mkdir my-channel-plugin
cd my-channel-plugin

# Initialize an npm project
npm init -y

# Install TypeScript
npm install typescript @types/node --save-dev

You can then initialize the TypeScript configuration and continue building the project.



Plugin Project Structure

A standard Channel Plugin project structure:

my-channel-plugin/
├── src/
│   ├── channel.ts         # Core implementation
│   ├── accounts.ts        # Account management
│   ├── config-schema.ts   # Configuration validation
│   ├── runtime.ts         # Runtime
│   ├── types.ts           # Type definitions
│   └── websocket-client.ts # WebSocket
├── scripts/
│   └── setup.mjs          # Installation script
├── index.ts               # Entry point
└── package.json

A more complete Yeizi project structure example:

yeizi/
├── web-channel/                    # Web project
│   ├── frontend/                   # Frontend project (Vue 3 + TypeScript)
│   │   ├── src/
│   │   │   ├── components/         # Vue components
│   │   │   ├── stores/             # Chat state management
│   │   │   └── App.vue             # Main app component
│   │   └── package.json
│   ├── backend/                    # Backend project (Express.js)
│   │   ├── src/
│   │   │   ├── routes/
│   │   │   │   ├── auth.ts         # Auth routes
│   │   │   │   └── config.ts       # Config query routes
│   │   │   ├── services/
│   │   │   │   ├── auth.ts         # Auth service
│   │   │   │   ├── config.ts       # Config service
│   │   │   │   └── websocket.ts    # WebSocket management
│   │   │   └── index.ts            # Service entry
│   │   ├── .env                    # Environment variables
│   │   └── package.json
│   └── package.json
│
└── yeizi-plugin/                   # OpenClaw plugin project
    ├── src/
    │   ├── accounts.ts             # Account management utilities
    │   ├── channel.ts              # Channel Plugin implementation
    │   ├── config-schema.ts
    │   ├── runtime.ts
    │   ├── types.ts
    │   └── websocket-client.ts
    ├── scripts/
    ├── index.ts
    └── package.json


Build and Install

# Build the plugin
npm run build

# Install the plugin
node scripts/setup.mjs your-app-key your-app-secret http://localhost:3000

# Restart OpenClaw
openclaw restart




Debugging and Testing

Logging

Use the log object provided by OpenClaw for logging:

log?.info(`[MyChannel] Message received`);
log?.warn(`[MyChannel] Warning message`);
log?.error(`[MyChannel] Error: ${error.message}`);

Common Troubleshooting

Issue 1: deliver callback is not triggered

Possible causes:

  1. OpenClaw version < 2026.3.12
  2. The AI model is not configured correctly
  3. blockStreaming configuration issue

Solutions:

  • Ensure the OpenClaw version is >= 2026.3.12
  • Check whether the AI model configuration is correct
  • Ensure blockStreaming: true

Issue 2: WebSocket connection fails

Checklist:

  • Is the backend service running?
  • Are AppKey / AppSecret correct?
  • Is the network connection working properly?

Issue 3: The AI does not reply

Checklist:

  • Is the AI model API key correct?
  • Is the model supported?
  • Can the network access the AI service?

Testing Recommendations

  1. Test the backend service locally first
  2. Start with simple message tests
  3. Gradually add more complex features
  4. Use logs to trace issues


Practical Example: The Yeizi Plugin

Yeizi is a Web Channel plugin used to connect a Web frontend and OpenClaw through WebSocket.

Key Implementation Points

The core of the Yeizi plugin is:

  1. Receive frontend messages through WebSocket
  2. Build ctxPayload and call dispatchReplyWithBufferedBlockDispatcher
  3. Send AI replies inside the deliver callback

Web Backend

The Yeizi plugin requires a Web backend service that provides:

  • /api/auth/token - authentication endpoint
  • /api/config - configuration query endpoint
  • /ws/plugin - plugin WebSocket endpoint
  • /ws - frontend WebSocket endpoint


Frequently Asked Questions

Q1: How should I choose a Channel ID?

A Channel ID should:

  • Uniquely identify the plugin
  • Use lowercase letters and numbers
  • Avoid conflicts with existing plugins
  • Be short and easy to remember

Q2: How do I support multiple accounts?

Add multiple account configurations in the config. Each account can represent a separate connection instance, and the plugin can choose the appropriate account based on the runtime context.

Q5: How do I publish the plugin?

# 1. Log in to NPM
npm login

# 2. Publish
npm publish --access public




Conclusion

Developing an OpenClaw Channel Plugin requires understanding its core concepts and architecture. Through this guide, you should now be able to:

  • Understand OpenClaw’s plugin system
  • Master the development workflow of a Channel Plugin
  • Implement a complete message channel plugin
  • Debug and publish the plugin

Happy coding!



API Endpoints

Backend API

EndpointMethodDescription
/api/configGETGet plugin configuration information
/api/auth/tokenPOSTPlugin authentication to obtain a token
/healthGETHealth check
/wsWebSocketFrontend connection endpoint
/ws/pluginWebSocketPlugin connection endpoint


Related Resources

  • Example plugin: Feishu plugin
  • Yeizi plugin source code


About the author

Ethan Carter
Ethan Carter

Ethan Carter is a recognized expert in the field of OpenClaw, a cutting-edge open-source framework for robotic manipulation. With a strong background in computer science and robotics, he has dedicated his career to advancing the capabilities of autonomous systems. Carter's work focuses on developing robust algorithms for grasping, object recognition, and path planning, pushing the boundaries of what's possible in robotic automation. His contributions have been instrumental in numerous projects, ranging from industrial applications to advanced research initiatives, making OpenClaw a more accessible and powerful tool for developers worldwide.

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