dsh-streaming-mcp-bridge
Bridges DeepSeek Harness streaming events to external clients via MCP and ACP, enabling real-time progress notifications for tool calls and status updates.
README
dsh-streaming-mcp-bridge
DeepSeek Harness 社区插件:把 Harness 的实时 session.event / session.status
流桥接给外部客户端,解决 ACP 只能返回最终结果、看不到思考/工具过程的问题。
- MCP 模式:Streamable HTTP,
dsh_run_stream执行任务时发送notifications/progress。 - ACP 模式:供 cc-connect / Feishu 使用,把思考、工具、状态实时推给飞书。
- Feishu 展示:每条状态、思考、工具调用/结果使用独立代码块,最终回答放在代码块外。
安装
作为 DSH bundle 插件安装到 Web profile:
dsh plugin --profile web add dsh-streaming-mcp-bridge
也可以固定使用 GitHub Release:
dsh plugin --profile web add github:yabolee-kkk/dsh-streaming-mcp-bridge#v0.1.0
或者从本地 checkout 安装:
dsh plugin --profile web add /path/to/dsh-streaming-mcp-bridge
安装后启动 DSH Web:
dsh web
MCP 默认监听:
http://127.0.0.1:3477/mcp
建议设置 Bearer token:
export DSH_STREAMING_MCP_TOKEN="your-secret-token"
配置
可通过 profile 的 cordis.patch.yml 覆盖:
- id: dsh-streaming-mcp-bridge
config:
host: 127.0.0.1
port: 3477
authTokenEnv: DSH_STREAMING_MCP_TOKEN
workspace: /home/you/workspace
provider: deepseek-official
model: deepseek-v4-flash
MCP 验证
curl -X POST http://127.0.0.1:3477/mcp \
-H 'Authorization: Bearer TOKEN' \
-H 'Content-Type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"curl","version":"1"}}}'
拿到 Mcp-Session-Id 后,先打开 GET SSE 流,再调用 dsh_run_stream,即可看到
notifications/progress。
ACP / Feishu 模式
cc-connect 的 dsh 项目可以直接使用:
[projects.agent]
type = "acp"
[projects.agent.options]
work_dir = "/home/you/workspace"
cmd = "<node>"
args = [
"<path-to-package>/bin/acp.js",
"--workspace",
"/home/you/workspace"
]
ACP 模式需要可用的 Harness JSON-RPC runtime。默认使用
DSH_HARNESS_HOME 下的源码路径,或通过 DSH_JSONRPC_BIN / DSH_CORDIS_CONFIG
指定运行环境。
安全
- MCP 默认只监听
127.0.0.1,不要直接暴露到公网。 - 使用 Bearer token 鉴权。
dsh_run_stream会让 Harness 执行真实任务,只对可信用户开放。
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
E2B
Using MCP to run code via e2b.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.