tiny-mcp-gateway

tiny-mcp-gateway

A zero-dependency MCP proxy/gateway server that aggregates multiple MCP servers, routes tools by prefix, load balances, and enforces authentication and rate limits.

Category
访问服务器

README

tiny-mcp-gateway

Zero-dependency MCP proxy/gateway server. Aggregate multiple MCP servers, route by tool prefix, load-balance, and enforce auth + rate limits. Like a reverse proxy for AI agent tool infrastructure.

pip install tiny-mcp-gateway   # coming soon

Why?

  • Multiple MCP servers — Claude Desktop, Cursor, and custom servers all need separate clients
  • No aggregation layer — no standard way to expose multiple MCP servers behind one endpoint
  • No routing — can't route github/* tools to a GitHub backend and file/* to a filesystem backend

tiny-mcp-gateway is one file that solves all three: proxy, router, load balancer, auth gateway — zero deps.

Quick Start

from tiny_mcp_gateway import MCPGateway, Backend

gw = MCPGateway(port=8080)

# Register backends
gw.add_backend(Backend(name="github",   url="https://api.github.com/mcp"))
gw.add_backend(Backend(name="files",     url="stdio:python -m mcp_fileserver"))
gw.add_backend(Backend(name="database",  url="https://db.internal/mcp"))

# Route by tool prefix
gw.route_tool("github/", "github",   priority=10)
gw.route_tool("file/",   "files",    priority=10)
gw.route_tool("db/",      "database", priority=10)
gw.set_default_backend("github")

# Generate an API key
key = gw.add_api_key(label="my-agent", rate_limit=100, scopes=["read"])

print(f"Gateway running. Key: {key}")

# Run the server
gw.run()  # starts on port 8080

Making Requests

curl -X POST http://localhost:8080/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "github/repo",
      "arguments": {"owner": "openai", "repo": "GPT-5"}
    }
  }'

Auth & Rate Limiting

# Create keys with different scopes and rate limits
gw.add_api_key(label="read-only-agent", scopes=["read"], rate_limit=50)
gw.add_api_key(label="full-agent",      scopes=["read", "write"], rate_limit=200)

# Pass key in params (works with all backends)
curl -X POST http://localhost:8080/mcp \
  -d '{"method": "tools/call", "params": {"name": "github/repo", "_api_key": "mcp_xxx"}}'

HMAC Signing (for webhook backends)

import os

# Set HMAC secret (shared with your backend)
os.environ["MCP_GATEWAY_HMAC_SECRET"] = "super-secret-key"

gw = MCPGateway(hmac_secret=os.environ["MCP_GATEWAY_HMAC_SECRET"])
gw.add_backend(Backend(
    name="secure-service",
    url="https://secure.internal/mcp",
    secret="super-secret-key",  # backend verifies HMAC signature
))
gw.run()

Architecture

Clients                          tiny-mcp-gateway
  |                                    |
  |-- POST /mcp (auth)  -----------> [Auth] --> [Router] --> [Backend Pool]
  |   tools/call github/repo               |            |
  |                                         v            v
  |-- GET  /health ---------> [Health]     [GitHub MCP]  [Files MCP]
  |-- GET  /routes --------> [Route Map]   [DB MCP]

Backend Types

HTTP Backend

gw.add_backend(Backend(name="api", url="https://api.example.com/mcp"))

Stdio Backend (local subprocess)

gw.add_backend(Backend(
    name="files",
    url="stdio:npx @anthropic/mcp-server-filesystem ./data"
))
gw.add_backend(Backend(
    name="github",
    url="stdio:python -m mcp_github --token $GITHUB_TOKEN"
))

Health & Monitoring

# Health check
curl http://localhost:8080/health
# {"status": "ok", "backends": [{"name": "github", "healthy": true, "failures": 0}]}

# Route map
curl http://localhost:8080/routes
# {"backends": [...], "routes": [{"prefix": "github/", "backend": "github", "priority": 10}]}

ASGI / WSGI Compatible

Works with any ASGI server (uvicorn, hypercorn) or as a plain Python module:

# uvicorn
import uvicorn
from tiny_mcp_gateway import MCPGateway
app = MCPGateway(port=8080)
uvicorn.run(app, host="0.0.0.0", port=8080)

# Or run directly
app.run()

AI Agent Fit

tiny-mcp-gateway is the backbone of a multi-tool agent architecture:

  • Single endpoint — agents connect to one gateway, access all tools
  • Tool routing — automatic routing by prefix, no manual tool dispatch
  • Load balancing — weighted round-robin across backend replicas
  • Circuit breaking — unhealthy backends are skipped automatically
  • Auth enforcement — per-key rate limits and scopes

This is the architecture that makes tiny-agent-service work with external MCP servers:

tiny-agent (reasoning) --> tiny-mcp-client --> tiny-mcp-gateway --> [MCP Servers]
                                                    |
                                                    +-> GitHub tools
                                                    +-> Filesystem tools
                                                    +-> Database tools

API Reference

Method Description
MCPGateway(port) Create gateway
gw.add_backend(Backend) Register a backend
gw.route_tool(prefix, backend, priority) Add routing rule
gw.set_default_backend(name) Set fallback backend
gw.add_api_key(label, scopes, rate_limit, ttl) Create API key
gw.run(host, port) Start server
gw.handle(scope, receive, send) ASGI entry point

Ecosystem

Part of the tiny-* zero-dependency toolkit for Python agent infrastructure:

All single-file, MIT, zero dependencies. Built by OpenClaw.

License

MIT © 2026 OpenClaw (hussain-alsaibai)

推荐服务器

Baidu Map

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。

官方
精选
JavaScript
Playwright MCP Server

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。

官方
精选
TypeScript
Magic Component Platform (MCP)

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。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

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。

官方
精选
本地
TypeScript
VeyraX

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。

官方
精选
本地
graphlit-mcp-server

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。

官方
精选
TypeScript
Kagi MCP Server

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。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

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。

官方
精选