MCP Gateway
A service orchestration layer for the Model Context Protocol. Manages multiple MCP services through a single unified interface — spawn, supervise, and route tool calls across all your services.
README
MCP Gateway
A service orchestration layer for the Model Context Protocol. Manages multiple MCP services through a single unified interface — spawn, supervise, and route tool calls across all your services.
Key Feature: Lazy Activate
By default, services activate in lazy mode — the process spawns and tool list is fetched, but zero tool schemas are injected into the LLM context. This means you can have hundreds of tools across dozens of services with no token overhead.
activate({name: "google-workspace"}) → 281 tools ready, 0 context tokens
tools({service: "google-workspace"}) → browse available tools
call({service: "...", tool: "...", args}) → call any tool directly
Features
- Lazy activate — spawn services with 0 context tokens, browse with
tools(), call withcall() - Service orchestration — spawn, stop, restart child MCP services
- On-demand tool browsing —
tools({service, filter})returns tool descriptions as conversation text (not system prompt) - Direct routing —
call()routes to child connections without needing schema registration - Environment variable expansion — use
$VARor${VAR}in config for secrets - Dynamic management — add/remove services at runtime without restarting
- Health monitoring — built-in ping/health checks
- Any command — supports
bun,node,npx,ssh, or any executable
Quick Start
# Install
bun install
# Create your config from the example
cp gateway.config.example.json gateway.config.json
# Edit gateway.config.json with your services
# Then start the gateway
bun run start
Configuration
gateway.config.json defines your services:
{
"services": [
{
"name": "my-service",
"command": "bun",
"args": ["run", "/path/to/service/index.ts"],
"env": { "API_KEY": "$MY_API_KEY" },
"autoActivate": false
}
]
}
| Field | Required | Default | Description |
|---|---|---|---|
name |
yes | — | Unique service identifier |
command |
yes | — | Executable to run (bun, node, npx, ssh, ...) |
args |
no | [] |
Command arguments |
env |
no | {} |
Environment variables (supports $VAR expansion) |
autoActivate |
no | false |
Start automatically on gateway launch |
keepAlive |
no | false |
Always-on: respawn with exponential backoff on crash; never GC'd when idle |
groups |
no | — | Named tool subsets for full-mode activation, e.g. {"gmail": ["send", "search"]} |
Environment Variables
Config values support $VAR and ${VAR} syntax, resolved from process.env at load time:
{
"env": { "API_KEY": "$MY_SECRET_KEY" },
"args": ["--config", "${HOME}/.config/my-service.json"]
}
This keeps secrets out of your config file. Pass them through your MCP client config (see below).
Built-in Tools
Once running, the gateway exposes these management tools:
| Tool | Description |
|---|---|
services |
List all services with status, mode (lazy/full), tool count, uptime |
activate |
Start a service. Default lazy (0 context tokens). Set lazy=false for full schema registration |
tools |
List available tools for an active service. Supports filter for keyword search |
deactivate |
Stop a service and clean up |
restart |
Kill and respawn a service (preserves lazy/full mode) |
health |
Ping all active services |
add |
Register a new service dynamically (persists to config) |
remove |
Remove a service from config |
call |
Call any tool on any active service |
Workflow
1. activate({name: "my-service"}) → spawn process, 0 tokens
2. tools({service: "my-service"}) → see all tools
3. tools({service: "my-service", filter: "search"}) → filter by keyword
4. call({service: "my-service", tool: "...", args: {}}) → call a tool
5. deactivate({name: "my-service"}) → stop when done
Full Mode (optional)
If you want tool schemas injected into the LLM context (traditional MCP behavior):
activate({name: "my-service", lazy: false}) → register all schemas
activate({name: "my-service", lazy: false, groups: ["gmail", "drive"]}) → register specific groups
HTTP Daemon Mode (always-on, shared)
Set GATEWAY_HTTP_PORT to run the gateway as a long-lived Streamable HTTP daemon instead of per-client stdio:
GATEWAY_HTTP_PORT=8770 bun run start
- Endpoint:
http://127.0.0.1:8770/mcp(Streamable HTTP,Mcp-Session-Idper client) - Health:
GET /healthreturns JSON with session count and per-service status/pid - Shared processes, isolated views: child services are spawned once and shared by every connected client; each session keeps its own tool registry, so one agent's full-mode activation never leaks into another's context
- Session GC: sessions idle longer than the TTL are swept automatically (clients often exit without sending DELETE). Tune with
GATEWAY_SESSION_TTL_MS(default 60 min) andGATEWAY_SESSION_SWEEP_MS(default 5 min) - Safe boot:
GATEWAY_NO_AUTOACTIVATE=1skipsautoActivateservices (e.g. when stateful singletons are already running elsewhere)
A systemd unit is provided in deploy/mcp-gateway.service.
Point Claude Code (or any MCP client) at the daemon:
{
"mcpServers": {
"gateway": { "type": "http", "url": "http://127.0.0.1:8770/mcp" }
}
}
Using with Claude Code
Add to your Claude Code MCP config (~/.claude/config.json or project settings).
API keys go in the env block — they're passed to the gateway process and expanded in gateway.config.json via $VAR syntax:
{
"mcpServers": {
"gateway": {
"command": "bun",
"args": ["run", "/path/to/mcp-gateway/src/index.ts"],
"env": {
"GEMINI_API_KEY": "your-gemini-key",
"EXA_API_KEY": "your-exa-key"
}
}
}
}
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。