MCP Gateway

Production-ready unified entry point for AI Agents and downstream APIs, implementing the Model Context Protocol (MCP).

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Quick Start (Local — 5 minutes)

Prerequisites

Tool	Minimum Version	Check
Python	3.10+	python3 --version
pip	23+	pip3 --version
make	any	make --version
Docker (optional)	24+	docker --version

macOS: Install Python via Homebrew: brew install python@3.12 Windows: Install Python from python.org, then use make via WSL or Git Bash.

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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 run

The gateway starts at http://localhost:8080.

Open the interactive API docs at http://localhost:8080/docs.

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Option B — Run with Docker Compose (full stack)

# Starts gateway + Redis + Prometheus + Grafana + Jaeger
make docker-up

Service	URL
Gateway API	http://localhost:8080
API Docs	http://localhost:8080/docs
Grafana	http://localhost:3000 (admin/admin)
Prometheus	http://localhost:9091
Jaeger (traces)	http://localhost:16686

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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 --reload

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Configuration

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=development

Add 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"]
  }
]

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Try It Out

Once the gateway is running, open a new terminal and try these:

Health check (no auth required)

curl http://localhost:8080/health

List 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"}'

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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 caches

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Project 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 template

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Authentication

The gateway supports three auth methods, all tried in order on each request:

Method	Header	Example
API Key	X-Api-Key	X-Api-Key: dev-key-alice-001
Agent Token	X-Agent-Token	X-Agent-Token: <jwt>
OAuth Bearer	Authorization	Authorization: Bearer <jwt>

Public paths (no auth needed): /health, /readyz, /metrics, /docs

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Key Endpoints

Endpoint	Method	Auth	Description
/health	GET	None	Liveness probe
/readyz	GET	None	Readiness + upstream health
/metrics	GET	None	Prometheus metrics
/docs	GET	None	Swagger UI
/mcp	POST	Required	MCP protocol endpoint
/mcp/{upstream}	POST	Required	Direct upstream proxy
/agents/register	POST	Required	Register AI agent
/agents/sessions	GET	Required	List active sessions
/upstreams	GET	Required	List configured upstreams
/config/info	GET	Required	Gateway configuration info

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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.

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Documentation

Full architecture document: docs/ARCHITECTURE.md