How does DeployStack make MCP servers available to HTTP clients?
It uses a satellite infrastructure that converts stdio-based MCP servers into HTTP/SSE endpoints, which can be consumed by any MCP client that supports HTTP transport.
@deploystackio
基本信息
Open source MCP hosting - deploy MCP servers to HTTP endpoints for n8n, Dify, Voiceflow, and any MCP client.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"deploystack": {
"type": "http",
"url": "https://satellite.deploystack.io/mcp"
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,直接连接服务器端点实时获取工具列表。
DeployStack is an open-source platform that hosts MCP (Model Context Protocol) servers as HTTP/SSE endpoints, integrating with GitHub to deploy any stdio MCP server in seconds. It is designed for users of workflow automation platforms like n8n, Dify, Voiceflow, Langflow, and AI coding tools like Claude Code and Cursor, eliminating the need for local setup or DevOps.
Sign up at cloud.deploystack.io, then deploy MCP servers from GitHub repositories or install from the curated catalog. Configure your MCP client with a single HTTP URL (e.g., https://satellite.deploystack.io/mcp) to access all team MCP tools. For self-hosting, run docker-compose up after cloning the repository.
It uses a satellite infrastructure that converts stdio-based MCP servers into HTTP/SSE endpoints, which can be consumed by any MCP client that supports HTTP transport.
The router exposes only two meta-tools (discover and execute), achieving up to 98% token reduction compared to loading all tools from multiple servers into context.
Credentials are stored in an encrypted vault at rest and automatically injected at runtime. They are never placed in config files or shared via Slack.
Yes, DeployStack is open-source under AGPL-3.0. You can run it on your own infrastructure using Docker Compose.
It works with any MCP client that supports HTTP/SSE, including n8n, Dify, Voiceflow, Langflow, Claude Code, Cursor, VS Code, Windsurf, and custom integrations.
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Model Context Protocol Servers
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
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