dsh-chatgpt-bridge

# dsh-chatgpt-bridge [](https://m8ven.ai/mcp/jiezeng2004-design-dsh-chatgpt-bridge-14d0zo) > **Let ChatGPT drive your local DSH agents.** > > 在 ChatGPT 里创建任务、继续会话、监督 Goal、处理审批并检查结果，不用在 ChatGPT 和 DSH 之间反复复制 Prompt。 `dsh-chatgpt-bridge` connects **ChatGPT Web → secure MCP tunnel → DeepSeek Harness (DSH)**. ChatGPT becomes the control surface; DSH keeps the agent loop, tools, skills, subagents, workflows, sandbox, approvals and workspace security model. **The bridge connects the two sides. It does not replace DSH, modify DSH core, or route DSH model traffic through ChatGPT.** Version **0.6.0** targets DSH **0.1.7-rc.2** exactly (the official npm `latest` at verification, itself a release candidate). Other DSH channels are outside this version's tested range. After a successful connection, ChatGPT should see **tool count = 23**. See the [compatibility evidence](docs/dsh-compatibility-2026-09-28.md). ## Why this exists A normal ChatGPT + local-agent workflow has too much manual glue: ```text Think in ChatGPT ↓ copy prompt to DSH ↓ wait / inspect logs ↓ copy result back ↓ review in ChatGPT ↓ repeat ``` With the bridge: ```text ChatGPT Web ↓ create / continue / supervise / approve Secure MCP tunnel ↓ dsh-chatgpt-bridge ↓ DeepSeek Harness ↓ local workspace + tools + agent runtime ``` You stay in ChatGPT while DSH remains the execution engine. ## What you can do from ChatGPT - create and inspect native DSH sessions; - send follow-up instructions without copying context between apps; - start, inspect, update and wait on Goals; - approve DSH actions through the bridge when your DSH policy requires it; - list registered workspaces and inspect runtime health; - keep using DSH's own sandbox, approval and workspace boundaries; - manage the supported tunnel runtime from the DSH Web settings UI. ## Real setup  The screenshot is from a real DSH Web installation with sensitive values masked. ## Quick start ### Requirements - Node.js 22+ - DeepSeek Harness `0.1.7-rc.2` (`dsh` on `PATH`) - a DSH Web profile/runtime - ChatGPT access that can use the currently supported MCP/custom-app connection flow ### 1. Install the plugin Install v0.6.0 into the matching DSH 0.1.7-rc.2 host: ```bash dsh plugin --profile web add dsh-chatgpt-bridge@0.6.0 ``` To install from a reviewed source checkout instead: ```bash npm ci npm run typecheck npm run build npm test npm run test:release pnpm dlx @deepseek-ai/dsh@0.1.7-rc.2 plugin --profile web add "file:$PWD" ``` Source installation into a real profile was not part of release verification. Back up the profile before upgrading DSH: DSH owns V3 session migration. `npm install dsh-chatgpt-bridge` alone is not enough: the plugin must be added to a DSH profile bundle. Published v0.5.1 remains tied to the older DSH 0.1.1-rc.2 host. ### 2. Start DSH Web ```bash dsh web ``` Keep DSH Web and the bridge in the **same web profile/runtime** so ChatGPT-created sessions appear live in the UI. Default local endpoints: | Service | Endpoint | | --- | --- | | DSH Web | `http://127.0.0.1:3080` | | Bridge MCP | `http://127.0.0.1:3456/mcp` | ### 3. Read the bridge token Windows PowerShell: ```powershell Get-Content "$HOME\.dsh\chatgpt-bridge.token" ``` macOS / Linux: ```bash cat ~/.dsh/chatgpt-bridge.token ``` Treat this token like a password. Do not commit it, post it, or paste it into public chats. Alternatively, set `DSH_CHATGPT_BRIDGE_TOKEN` yourself and the bridge uses it instead of generating a file. ### 4. Connect ChatGPT ChatGPT Web cannot reach a plain localhost MCP endpoint directly. Use the secure MCP/tunnel connection mechanism currently supported by OpenAI and forward it to: ```text http://127.0.0.1:3456/mcp ``` Use the bridge token as the MCP bearer credential where the connection flow requires it. The bridge keeps a localhost-first design: it binds `127.0.0.1`, never exposes a public interface, and never self-hosts a tunnel. ### 5. Refresh tools and verify After connecting, refresh/rescan the MCP tools in ChatGPT and run a read-only check: ```text 请使用已连接的 DSH App，只做只读检查： 1. 调用 dsh_health 2. 调用 dsh_list_workspaces 3. 不修改任何文件 4. 返回 bridge version、health 和 workspace 名称 ``` A healthy first check should look like: ```text bridge version = 0.6.0 tool count = 23 ``` If health is OK, the version matches, and your registered workspace appears, the control path is ready. ## First useful workflow A practical pattern is: ```text ChatGPT: define the task and constraints ↓ Bridge: create / start a DSH Goal ↓ DSH: execute inside its registered workspace ↓ Bridge: wait, inspect status, surface approvals ↓ ChatGPT: review the result and decide what happens next ``` For a safe first run, start with a read-only Goal: ```text 使用 DSH App 创建一个只读检查目标： - workspace 使用 dsh_list_workspaces 查到的已注册工作区 - goal：只读检查项目 - constraints：read_only=true - 列出项目结构并总结 README - 等待目标结束后只汇报结果，不修改任何文件 ``` ## Security model This is a **control bridge**, not a remote shell replacement. - The MCP server binds to loopback by default. - It binds `127.0.0.1`, never exposes a public interface, and never self-hosts a tunnel. - DSH remains responsible for its own sandbox, approvals and workspace rules. - The bridge only works with workspaces already registered in DSH. - Tokens and tunnel/runtime secrets are stored outside the repository and should never be committed. - Write/action tools are real actions. Keep approval policies appropriate for the workspace you expose. - Tunnel/runtime management is designed to fail closed around process ownership and lifecycle ambiguity. If you only need inspection, use read-only prompts and keep DSH constraints read-only. ## What this project is not - It is **not** a ChatGPT API proxy. - It does **not** make DSH use your ChatGPT subscription as a model provider. - It does **not** upload an arbitrary workspace to ChatGPT. - It does **not** bypass DSH approvals or sandboxing. - It does **not** modify DeepSeek Harness core. ## Troubleshooting ### ChatGPT cannot connect `127.0.0.1` only exists on your machine. Confirm that your supported secure tunnel/MCP connection forwards to the bridge endpoint and that the bridge token matches the running DSH profile. ### `401 Unauthorized` Re-read the token from the active DSH home/profile and make sure the connector sends the matching bearer credential. ### No workspace appears The bridge only lists **registered DSH workspaces**. Register the project in DSH first; the bridge intentionally does not auto-register arbitrary filesystem paths. ### Session exists but is not live in DSH Web Run the bridge and DSH Web in the same web profile/runtime. Separate runtimes may persist sessions but will not provide the same live UI behavior. ### Tool list looks stale Restart/upgrade the plugin as needed, then refresh/rescan the MCP tools on the ChatGPT side. ## Project status This is an actively maintained, independent DSH plugin. Compatibility releases track DeepSeek Harness changes while preserving the bridge's MCP/tool semantics and security boundaries. Current source version: ```text dsh-chatgpt-bridge@0.6.0 ``` Compatibility: **v0.6.0 → DSH 0.1.7-rc.2**. The exact release commit passed Ubuntu and Windows CI on Node 22 and 24, including a packed-package install and model-free official DSH CLI/Web/MCP integration. Browser UI, real-model work, ChatGPT and tunnel end-to-end remain unverified for this version. The older published v0.5.1 package targets DSH 0.1.1-rc.2. Distribution and ecosystem listings: - [npm](https://www.npmjs.com/package/dsh-chatgpt-bridge) - [M8ven](https://m8ven.ai/mcp/jiezeng2004-design-dsh-chatgpt-bridge-14d0zo) - [dshbase](https://dshbase.com/plugins/dsh-chatgpt-bridge/) - [DSHarness](https://dsharness.org/plugin/jiezeng2004-design/dsh-chatgpt-bridge) Third-party directory labels describe those directories' own checks; they are not security audits or endorsements. ## Development The bridge is a standalone DSH plugin with no DSH core modifications. Development focuses on: - MCP tool/schema compatibility; - Goal/session lifecycle reliability; - native settings and tunnel runtime management; - process-ownership safety; - regression and compatibility testing across supported DSH releases. Before publishing a new version, run `npm run typecheck`, `npm run build`, `npm test` and `npm run test:release`. The last command installs the actual tarball and exact DSH host in a disposable directory. ## License MIT. See [LICENSE](LICENSE). --- **Unofficial community project. Not affiliated with or endorsed by OpenAI or DeepSeek.**