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dsh-feishu-bridge

Client Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install ailoushu666/dsh-feishu-bridge

Paste the following prompt into your AI chat to install this plugin:

Execute the command dsh plugin install ailoushu666/dsh-feishu-bridge in DeepSeek Harness to install this plugin, with source code hosted at https://github.com/ailoushu666/dsh-feishu-bridge.

About this plugin

dsh-feishu-bridge addresses the disconnect between local AI workflows and instant messaging tools. By establishing a WebSocket long connection, it bridges Feishu directly with the locally running DeepSeek Harness, eliminating the need for public IPs or complex tunneling setups. This allows you to interact with AI entirely within the familiar Feishu interface without constantly switching between your browser or terminal, significantly enhancing workflow continuity.

Regarding its core capabilities, the plugin not only maintains context for multi-turn conversations but also provides real-time visibility into the Agent's "thinking process." Seeing 🔧 Tool Calls or 💬 Intermediate Replies means the AI is actively utilizing tools to solve problems rather than just generating a final answer. Additionally, built-in Feishu-side commands allow you to switch models, adjust reasoning effort, or manually stop tasks on the fly, making complex local Agent debugging accessible and intuitive.

This plugin is ideal for developers and technical researchers who need deep debugging capabilities and local deployment, as well as teams looking to integrate powerful local Large Language Models into their daily work. Whether for code review, data analysis, or executing complex automation tasks, it provides a human-like interactive experience while strictly ensuring data privacy and local control.

Screenshots

Use Cases

  • Control local DeepSeek Agent via Feishu
  • Debug tool calls in real-time within group chats
  • Switch models and reasoning effort using Feishu commands

Best For

  • Developers needing local AI debugging within Feishu
  • Researchers prioritizing data privacy and local LLM execution
  • Teams seeking to seamlessly embed powerful AI into daily collaboration