MCP Gateway
Acts as a gateway to proxy Model Context Protocol (MCP) requests to Notion, allowing AI agents to interact with Notion tools and data through a unified entry point.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Gatewaylist all configured upstream APIs"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Gateway
Production-ready unified entry point for AI Agents and downstream APIs, implementing the Model Context Protocol (MCP).
Quick Start (Local — 5 minutes)
Prerequisites
Tool | Minimum Version | Check |
Python | 3.10+ |
|
pip | 23+ |
|
make | any |
|
Docker (optional) | 24+ |
|
macOS: Install Python via Homebrew:
brew install python@3.12Windows: Install Python from python.org, then usemakevia WSL or Git Bash.
Option A — Run with Python directly (recommended for development)
# 1. Clone / open the project folder
cd mcp-gateway
# 2. One-command setup (creates virtualenv + installs deps + copies .env)
make setup
# 3. Start the gateway
make runThe gateway starts at http://localhost:8080.
Open the interactive API docs at http://localhost:8080/docs.
Option B — Run with Docker Compose (full stack)
# Starts gateway + Redis + Prometheus + Grafana + Jaeger
make docker-upService | URL |
Gateway API | |
API Docs | |
Grafana | http://localhost:3000 (admin/admin) |
Prometheus | |
Jaeger (traces) |
Manual Setup (step by step)
If you prefer not to use make:
# 1. Create virtual environment
python3 -m venv .venv
source .venv/bin/activate # macOS/Linux
# .venv\Scripts\activate # Windows
# 2. Install dependencies
pip install -e ".[dev]"
# 3. Copy environment config
cp .env.example .env
# 4. Create log directory
mkdir -p logs
# 5. Start the gateway
uvicorn src.main:app --host 0.0.0.0 --port 8080 --reloadConfiguration
All configuration is in the .env file (copied from .env.example during setup).
Key settings
# Auth — who can call the gateway
GATEWAY_AUTH_ENABLED=true
GATEWAY_API_KEYS_FILE=config/api_keys.json # your API keys
# Upstream APIs — what the gateway proxies to
GATEWAY_UPSTREAM_CONFIG_FILE=config/upstreams.json
# Rate limiting
GATEWAY_RATE_LIMIT__DEFAULT_RPM=60 # requests per minute per identity
GATEWAY_RATE_LIMIT__BURST_ALLOWANCE=10
# Debug / dev mode
GATEWAY_DEBUG=true
GATEWAY_ENVIRONMENT=developmentAdd your own upstream API
Edit config/upstreams.json:
[
{
"name": "my-api",
"url": "https://api.example.com",
"description": "My downstream API",
"upstream_token": "your-bearer-token-here",
"timeout_seconds": 30,
"tags": ["internal"]
}
]Add an API key
Edit config/api_keys.json:
[
{
"key": "my-secret-key-001",
"owner": "your-name",
"allowed_upstreams": [],
"rate_limit_rpm": -1,
"scopes": ["read", "write"]
}
]Try It Out
Once the gateway is running, open a new terminal and try these:
Health check (no auth required)
curl http://localhost:8080/healthList configured upstreams
curl http://localhost:8080/upstreams \
-H "X-Api-Key: dev-key-alice-001"Send an MCP initialize request
curl -X POST http://localhost:8080/mcp \
-H "Content-Type: application/json" \
-H "X-Api-Key: dev-key-alice-001" \
-d '{
"version": "1.0",
"request": {
"jsonrpc": "2.0",
"id": 1,
"method": "initialize",
"params": {
"protocolVersion": "2024-11-05",
"clientInfo": {"name": "my-agent", "version": "1.0"}
}
}
}'Register an AI agent (get a session token)
curl -X POST http://localhost:8080/agents/register \
-H "Content-Type: application/json" \
-H "X-Api-Key: dev-key-alice-001" \
-d '{
"agent_name": "my-llm-agent",
"agent_version": "1.0.0",
"requested_upstreams": [],
"requested_scopes": ["read", "write"]
}'Use agent token to call MCP
# Replace <token> with the token from the register response
curl -X POST http://localhost:8080/mcp \
-H "Content-Type: application/json" \
-H "X-Agent-Token: <token>" \
-d '{
"request": {
"jsonrpc": "2.0",
"id": 2,
"method": "tools/list"
}
}'Proxy directly to an upstream
curl -X POST http://localhost:8080/mcp/notion \
-H "Content-Type: application/json" \
-H "X-Api-Key: dev-key-alice-001" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'Common Commands
make run # Start gateway (http://localhost:8080)
make run-reload # Start with hot-reload (auto-restarts on code change)
make test # Run all tests
make test-unit # Run unit tests only
make lint # Lint code with ruff
make format # Auto-format code
make typecheck # Type check with mypy
make docker-up # Start full stack (gateway + Redis + monitoring)
make docker-down # Stop Docker stack
make clean # Remove virtualenv and cachesProject Structure
mcp-gateway/
├── src/
│ ├── main.py ← Entry point
│ ├── core/
│ │ ├── app.py ← App factory + middleware wiring
│ │ ├── config.py ← All configuration (env + JSON)
│ │ └── state.py ← Shared HTTP pool + rate buckets
│ ├── protocol/
│ │ ├── mcp_types.py ← MCP message types
│ │ └── validator.py ← Request validation pipeline
│ ├── routing/
│ │ ├── mcp_router.py ← MCP method handling
│ │ └── proxy.py ← Reverse proxy with retries
│ ├── security/
│ │ ├── auth.py ← API Key + OAuth JWT + Agent auth
│ │ └── agent_registry.py ← Agent session management
│ ├── middleware/
│ │ ├── rate_limiter.py ← Token-bucket rate limiting
│ │ ├── logging_mw.py ← Structured JSON access logs
│ │ └── circuit_breaker.py ← Per-upstream circuit breaker
│ └── observability/
│ ├── telemetry.py ← OpenTelemetry + Prometheus
│ └── health.py ← /health, /readyz, /metrics
├── config/
│ ├── api_keys.json ← API credentials
│ └── upstreams.json ← Downstream API definitions
├── tests/
│ ├── unit/ ← Fast, isolated tests
│ └── integration/ ← Full stack tests
├── deploy/k8s/ ← Kubernetes manifests
├── monitoring/ ← Prometheus + Grafana configs
├── Dockerfile ← Multi-stage production image
├── docker-compose.yml ← Local dev stack
├── Makefile ← Developer commands
└── .env.example ← Config templateAuthentication
The gateway supports three auth methods, all tried in order on each request:
Method | Header | Example |
API Key |
|
|
Agent Token |
|
|
OAuth Bearer |
|
|
Public paths (no auth needed): /health, /readyz, /metrics, /docs
Key Endpoints
Endpoint | Method | Auth | Description |
| GET | None | Liveness probe |
| GET | None | Readiness + upstream health |
| GET | None | Prometheus metrics |
| GET | None | Swagger UI |
| POST | Required | MCP protocol endpoint |
| POST | Required | Direct upstream proxy |
| POST | Required | Register AI agent |
| GET | Required | List active sessions |
| GET | Required | List configured upstreams |
| GET | Required | Gateway configuration info |
Troubleshooting
ModuleNotFoundError: No module named 'src'
→ Make sure you're in the mcp-gateway/ directory, not a subdirectory.
→ Run pip install -e ".[dev]" from the project root.
401 Unauthorized
→ Add header -H "X-Api-Key: dev-key-alice-001" to your requests.
→ Check config/api_keys.json contains the key you're using.
Address already in use (port 8080)
→ Change the port: uvicorn src.main:app --port 8090
→ Or update GATEWAY_PORT=8090 in your .env file.
429 Too Many Requests
→ You've hit the rate limit. Wait a minute or increase GATEWAY_RATE_LIMIT__DEFAULT_RPM in .env.
Documentation
Full architecture document: docs/ARCHITECTURE.md
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