gpt-dsh-bridge
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@gpt-dsh-bridgeSubmit a task to deploy the new model version"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
GPT↔DSH Bridge
A bridge for ChatGPT web to drive DeepSeek Harness (DSH) for automated task execution.
GPT is the commander, DSH is the executor. An MCP protocol links them together.
English · 中文 | MIT License
Quick Start
git clone https://github.com/baochaofan0404/gpt-dsh-bridge.git
cd gpt-dsh-bridge
pnpm install
pnpm build
pnpm startThen connect to the exposed https://<tunnel>/mcp endpoint via ChatGPT Developer Mode (Connectors → Add MCP), and you can use tools like dsh_task_submit in the conversation to drive DSH to execute tasks.
Architecture
┌─────────────────┐ HTTPS MCP ┌──────────────────────────┐ ACP ┌──────────┐
│ ChatGPT Web │ ─────────────────► │ Bridge Orchestrator │ ───────────► │ DSH │
│ (MCP Host) │ │ (Node · Windows/WSL) │ stdio RPC │ (WSL) │
└─────────────────┘ │ │ └──────────┘
▲ │ · 13 MCP 工具 │
│ 结果回投(模型自然写入对话) │ · 任务状态机 │
│ │ · conversation↔session │
└───────────────────────────────────┘ 映射 + 持久化 │Core Design Principles:
DSH stays untouched: reuse the existing ACP server, zero intrusion
Bridge is a thin layer: only task orchestration, state management, and protocol adaptation
ChatGPT side connects via native Developer Mode MCP (channel verified at
E:\mcpgpt)
MCP Tool Contract (currently 13)
工具 | 用途 |
| Submit a new task, returns taskId |
| Query task status |
| Get the final task result |
| Cancel a running task |
| Revise based on current results and re-execute |
| Manually approve HUMAN_REQUIRED tasks |
| Manually review task results |
| List all tasks under a project |
| Create/switch workspace project |
| View project status |
| List DSH sessions |
| Archive completed sessions |
| Rotate DSH session (when context is too long) |
Task State Machine
CREATED → SUBMITTED → RUNNING → SUCCESS → COMPLETED
↘ FAILED
↘ TIMEOUT
↘ CRASHED
↘ CANCELLED
↘ HUMAN_REQUIRED → (approve) → RUNNING
→ (reject) → CANCELLEDSee designs/state-machine.md for the complete state machine definition.
Directory Structure
gpt-dsh-bridge/
├── src/
│ ├── mcp/ # MCP server + 13 个工具实现
│ ├── task/ # TaskManager + TaskStore(SQLite)
│ ├── workspace/ # 项目/工作区管理
│ ├── errors.ts # BridgeError + error codes
│ └── config.ts # 配置加载
├── designs/ # 架构设计文档
├── docs/ # 用户文档
├── scripts/ # 启动/隧道脚本
└── recon/ # 侦察报告(原始研究材料)Dependencies
Node.js ≥ 22
DeepSeek Harness (DSH) installed and running (
pnpm dsh --profile web)OpenAI MCP Tunnel or cloudflared (HTTPS tunnel)
ChatGPT Developer Mode (Pro/Plus/Enterprise)
License
MIT © 2026 baochaofan0404
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