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Agent Client Protocol (ACP) server for DeepSeek Harness with real-time streaming, thought visibility, tool lifecycle updates, and session recovery.","maintainers":[{"name":"hobby0524","email":"hobby0524@gmail.com"}],"readme":"# DeepSeek Harness ACP 协议独立服务\n\n[![npm version](https://img.shields.io/npm/v/deepseek-harness-acp.svg?color=blue)](https://www.npmjs.com/package/deepseek-harness-acp)\n[![npm downloads](https://img.shields.io/npm/dm/deepseek-harness-acp.svg)](https://www.npmjs.com/package/deepseek-harness-acp)\n[![license](https://img.shields.io/npm/l/deepseek-harness-acp.svg)](LICENSE)\n\n> 基于 DeepSeek Harness 构建的轻量级独立 Agent Client Protocol (ACP) 服务端。支持实时 Token 打字机流、深度思考链流式输出、工具执行生命周期卡片、跨进程历史会话恢复与动态模型切换。\n\n[English](README.md)\n\n\n---\n\n## ✨ 核心特性\n\n- **⚡ 实时打字机 Token 流**：逐字返回（`agent_message_chunk`），极致响应体验。\n- **🧠 思考链 / 深度思考流**：实时查看模型推理思考过程（`agent_thought_chunk`）。\n- **📊 完整用量与性能指标**：`session/prompt` 响应返回标准 `usage`（输入/输出/Cache命中/思考Token）与 `_meta.metrics`（轮步数、TTFT首字延迟、tok/s生成速度、缓存命中率）。\n- **🛠️ 工具执行生命周期**：完整的工具调用中与完成状态更新（`tool_call` & `tool_call_update`）。\n- **🧩 MCP (Model Context Protocol) 扩展**：支持 Stdio / Streamable HTTP 外部 MCP 服务，自动发现项目 `.mcp.json` / `.cursor/mcp.json` / `.vscode/mcp.json` 与 ACP 会话参数，无缝扩充 Agent 工具生态。Harness 0.1.6 不支持旧版 SSE 传输。\n- **🔄 跨进程会话恢复与列表**：支持多轮对话接续与历史会话读取（`session/load`、`session/resume`、`session/list`）。\n\n- **⚙️ 动态配置项**：支持客户端动态切换模型（`deepseek-v4-pro` / `deepseek-v4-flash`）。\n- **📦 零配置开箱即用**：内置默认沙箱与智能体配置，只需配置 `DEEPSEEK_API_KEY` 即可一行命令启动。\n\n---\n\n## 🚀 快速开始\n\n### 1. 全局安装（CLI）\n\n需要 Node.js 24 或更高版本，使用 DeepSeek Harness `0.1.6-alpha.2`。\n\n```bash\n# 全局安装（支持全称或短别名）\nnpm install -g deepseek-harness-acp\n# 或\nnpm install -g dsh-acp\n\n# 或直接免安装秒级运行\nnpx dsh-acp\n# 或\nnpx deepseek-harness-acp\n```\n\n### 2. 配置环境变量\n\n创建 `.env` 文件或直接导出环境变量：\n\n```bash\nexport DEEPSEEK_API_KEY=\"sk-your-api-key\"\n# 可选环境变量：\nexport DEEPSEEK_BASE_URL=\"https://api.deepseek.com\"\nexport DEEPSEEK_PROTOCOL=\"messages\" # messages（默认）| chat-completions\nexport DEEPSEEK_MODEL=\"deepseek-v4-pro\"\nexport DSH_PERMISSION_MODE=\"workspace-write\" # workspace-write | danger-full-access\n```\n\n---\n\n## 🔌 第三方客户端接入指南\n\n### Zed 编辑器\n\n在 Zed 配置文件（`~/.config/zed/settings.json`）中添加：\n\n```json\n{\n  \"assistant\": {\n    \"version\": \"2\",\n    \"custom_agents\": [\n      {\n        \"name\": \"DeepSeek Harness\",\n        \"command\": \"deepseek-harness-acp\",\n        \"env\": {\n          \"DEEPSEEK_API_KEY\": \"sk-your-deepseek-api-key\"\n        }\n      }\n    ]\n  }\n}\n```\n\n### FreeBuddy\n\n在 FreeBuddy 设置中指定：\n- **执行命令**：`deepseek-harness-acp`（或 `dsh-acp`）\n- **环境变量**：`DEEPSEEK_API_KEY=sk-...`\n\n### Node.js / TypeScript 代码集成\n\n```typescript\nimport { spawn } from 'node:child_process'\nimport { ClientSideConnection, ndJsonStream } from '@agentclientprotocol/sdk'\n\nconst proc = spawn('deepseek-harness-acp', [], {\n  env: { ...process.env, DEEPSEEK_API_KEY: 'sk-your-api-key' },\n  stdio: ['pipe', 'pipe', 'inherit'],\n})\n\nconst stream = ndJsonStream(proc.stdin, proc.stdout)\nconst client = new ClientSideConnection(\n  (agent) => ({\n    sessionUpdate: async ({ update }) => {\n      if (update.sessionUpdate === 'agent_message_chunk') {\n        process.stdout.write(update.content.text) // 实时打字机输出\n      } else if (update.sessionUpdate === 'agent_thought_chunk') {\n        process.stderr.write(update.content.text) // 思考流\n      }\n    },\n    requestPermission: async () => ({ outcome: { outcome: 'selected', optionId: 'allow-once' } }),\n  }),\n  stream,\n)\n\nawait client.initialize({ protocolVersion: 1, clientCapabilities: {} })\nconst { sessionId } = await client.newSession({ cwd: process.cwd(), mcpServers: [] })\n\nawait client.prompt({\n  sessionId,\n  prompt: [{ type: 'text', text: '你好，DeepSeek！' }],\n})\n```\n\n---\n\n## 🧩 MCP (Model Context Protocol) 配置指南\n\n`deepseek-harness-acp` 原生支持作为 **MCP Client** 连接外部 MCP 服务器并将其提供的工具注册给 DeepSeek 智能体：\n\n### 1. 工作区配置文件自动加载\n\n在项目工作区根目录下创建 `.mcp.json`（或 `.cursor/mcp.json` / `.vscode/mcp.json`）：\n\n```json\n{\n  \"mcpServers\": {\n    \"github\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@modelcontextprotocol/server-github\"],\n      \"env\": {\n        \"GITHUB_PERSONAL_ACCESS_TOKEN\": \"ghp_...\"\n      }\n    },\n    \"fetch\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@modelcontextprotocol/server-fetch\"]\n    },\n    \"remote-http\": {\n      \"type\": \"http\",\n      \"url\": \"http://localhost:8080/mcp\"\n    }\n  }\n}\n```\n\n### 2. ACP 会话参数动态传入\n\n当编辑器发起 `session/new` 或 `session/resume` 请求时，在参数中携带 `mcpServers` 列表，服务会自动连接并将工具注入 DeepSeek 的决策上下文中。\n\n---\n\n\n## 📜 协议方法清单\n\n| 方法 / 通知 | 说明 |\n|---|---|\n| `initialize` | 协议协商（公布 `loadSession: true`、`sessionCapabilities.close/list/resume`） |\n| `session/new` | 创建新会话并返回初始可用配置项 |\n| `session/load` | 跨进程加载历史会话并重构上下文 |\n| `session/resume` | 恢复已有活跃或持久化会话 |\n| `session/list` | 列出已知会话并支持按工作区 `cwd` 过滤 |\n| `session/set_config_option` | 动态修改会话配置项（如切换模型） |\n| `session/prompt` | 发送用户提问并等待 Agent 执行完毕 |\n| `session/cancel` | 中途取消/打断正在处理的提问 |\n| `session/close` | 主动释放会话资源 |\n| `session/update` *(流式推送)* | 实时接收文本分片、思考链分片与工具执行状态 |\n\n---\n\n## 📄 开源许可\n\n[MIT](LICENSE) © maojindao55\n","readmeFilename":"README.zh.md"}