Sipap

Production-ready MCP server framework for AWS Lambda and ECS Fargate

Python Version Type Checked Code Style Test Coverage Tests

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Overview

sipap-mcp provides base classes and infrastructure for building Model Context Protocol (MCP) servers that implement JSON-RPC 2.0 and can run on:

• AWS Lambda: Serverless functions for lightweight, sporadic workloads
• ECS Fargate: Containerized services for long-running, stateful workloads

This framework powers all 5 data servers in the SIPAP (Sports Intelligence Platform) architecture, handling sports data, odds intelligence, news context, weather data, and historical statistics.

Features

Core Functionality

• ✅ MCPServer Base Class: Abstract base with tool registration and auto-discovery
• ✅ @mcp_tool Decorator: Mark functions as MCP tools with JSON Schema validation
• ✅ JSON-RPC 2.0 Protocol: Complete implementation with proper error handling
• ✅ Dual Transport: Lambda handler and FastAPI HTTP server

Security & State

• ✅ Authentication: Pluggable strategies (NoAuth, API key, AWS SigV4)
• ✅ Session Management: Redis-backed state preservation between calls
• ✅ Input Validation: JSON Schema validation on all tool inputs

Quality

• ✅ Type Safety: Full mypy strict mode compliance (zero errors)
• ✅ Test Coverage: 96% coverage with 112 passing tests
• ✅ Production Ready: Zero linting errors, comprehensive error handling

Installation

pip install sipap-mcp

For development:

pip install sipap-mcp[dev]

Quick Start

1. Define an MCP Server

from sipap_mcp import MCPServer, mcp_tool

class WeatherMCP(MCPServer):
    """Weather data MCP server."""

    def __init__(self):
        super().__init__(name="weather-mcp", version="1.0.0")

    @mcp_tool(
        description="Get current weather for a location",
        input_schema={
            "type": "object",
            "properties": {
                "location": {"type": "string", "description": "City name"},
                "units": {
                    "type": "string",
                    "enum": ["celsius", "fahrenheit"],
                    "default": "celsius"
                }
            },
            "required": ["location"]
        }
    )
    def get_weather(self, location: str, units: str = "celsius") -> dict:
        """Get current weather conditions."""
        # Your implementation here
        return {
            "location": location,
            "temperature": 22 if units == "celsius" else 72,
            "units": units,
            "condition": "partly cloudy"
        }

2. Deploy to AWS Lambda

from sipap_mcp.transport import create_lambda_handler
from sipap_mcp.auth import APIKeyAuth

# Create server instance
server = WeatherMCP()

# Configure authentication
auth = APIKeyAuth(api_keys=["your-api-key"])

# Create Lambda handler (entry point for AWS)
handler = create_lambda_handler(server, auth=auth)

Deploy with AWS CDK or Terraform:

• Handler: your_module.handler
• Runtime: python3.12
• Timeout: 30 seconds

3. Deploy to ECS Fargate (HTTP)

from sipap_mcp.transport import create_http_app
import uvicorn

# Create server instance
server = WeatherMCP()

# Create FastAPI app
app = create_http_app(server, auth=auth)

# Run with uvicorn
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)

Deploy with Docker:

FROM python:3.12-slim
WORKDIR /app
COPY . .
RUN pip install sipap-mcp
CMD ["uvicorn", "your_module:app", "--host", "0.0.0.0", "--port", "8000"]

Core Concepts

Tools

Tools are functions decorated with @mcp_tool that become callable via the MCP protocol:

@mcp_tool(
    description="Description of what this tool does",
    input_schema={
        "type": "object",
        "properties": {
            "param": {"type": "string"}
        },
        "required": ["param"]
    }
)
def my_tool(self, param: str) -> dict:
    """Docstring for the tool."""
    return {"result": param}

JSON Schema types supported:

• string, number, integer, boolean, array, object
• Validation: minLength, maxLength, minimum, maximum, pattern, enum

Authentication

Choose the authentication strategy that fits your deployment:

NoAuth (Development Only)

from sipap_mcp.auth import NoAuth

auth = NoAuth()  # No authentication - use for local dev only

API Key Authentication

from sipap_mcp.auth import APIKeyAuth

auth = APIKeyAuth(api_keys=[
    "client-a-key",
    "client-b-key",
    "client-c-key"
])

Clients send API key in X-API-Key header.

AWS SigV4 Authentication

from sipap_mcp.auth import SigV4Auth

auth = SigV4Auth(service="lambda", region="us-east-1")

For Lambda Function URLs with IAM authentication.

Session Management

Maintain state across multiple requests using Redis:

import redis
from sipap_mcp.session import SessionManager

# Connect to Redis
redis_client = redis.Redis(host="localhost", port=6379)

# Create session manager
session_manager = SessionManager(
    redis_client=redis_client,
    ttl=3600  # 1 hour default
)

# Create session
session_id = session_manager.create_session(
    data={"user_id": "123", "preferences": {...}},
    ttl=1800  # 30 minutes custom TTL
)

# Retrieve session
session_data = session_manager.get_session(session_id)

# Update session
session_manager.update_session(session_id, updated_data)

# Extend TTL
session_manager.extend_ttl(session_id, ttl=7200)

Lifecycle Hooks

Override _setup() and _cleanup() for resource management:

class MyServer(MCPServer):
    def __init__(self):
        super().__init__(name="my-server", version="1.0.0")
        self.db_connection = None

    def _setup(self) -> None:
        """Called when entering context manager."""
        self.db_connection = connect_to_database()

    def _cleanup(self) -> None:
        """Called when exiting context manager."""
        if self.db_connection:
            self.db_connection.close()

Use with context manager:

with server:
    # Server is set up, resources initialized
    response = server.handle_request(request)
    # Cleanup happens automatically on exit

JSON-RPC 2.0 Protocol

Request Format

List Available Tools

{
  "jsonrpc": "2.0",
  "id": "req-1",
  "method": "tools/list",
  "params": {}
}

Response:

{
  "jsonrpc": "2.0",
  "id": "req-1",
  "result": {
    "tools": [
      {
        "name": "get_weather",
        "description": "Get current weather for a location",
        "inputSchema": {
          "type": "object",
          "properties": {...},
          "required": [...]
        }
      }
    ]
  }
}

Call a Tool

{
  "jsonrpc": "2.0",
  "id": "req-2",
  "method": "tools/call",
  "params": {
    "name": "get_weather",
    "arguments": {
      "location": "London",
      "units": "celsius"
    }
  }
}

Response:

{
  "jsonrpc": "2.0",
  "id": "req-2",
  "result": {
    "content": [{
      "type": "text",
      "text": "{\"location\": \"London\", \"temperature\": 15, ...}"
    }]
  }
}

Error Handling

Standard JSON-RPC 2.0 error codes:

Code	Meaning	When
-32700	Parse error	Invalid JSON
-32600	Invalid Request	Missing required fields
-32601	Method not found	Unknown method
-32602	Invalid params	Validation failed
-32603	Internal error	Server error

Error Response:

{
  "jsonrpc": "2.0",
  "id": "req-3",
  "error": {
    "code": -32602,
    "message": "Invalid params: 'location' is required"
  }
}

Examples

See the examples/ directory for comprehensive examples:

Example	Description
01_basic_server.py	Simple calculator server
02_lambda_with_auth.py	Lambda deployment with API key auth
03_http_with_sessions.py	HTTP server with Redis sessions
04_advanced_server.py	Advanced patterns & lifecycle hooks
05_authentication.py	All authentication strategies

Run examples:

python examples/01_basic_server.py
python examples/02_lambda_with_auth.py
python examples/03_http_with_sessions.py  # Requires Redis

Architecture

Design Patterns (from Sentinel)

This framework adapts proven patterns from the Sentinel architecture:

1. ExitStack + Generator Pattern: Resource management with context managers
2. Tool Auto-Discovery: Introspection-based tool registration
3. Structured Output Enforcement: JSON Schema validation on all inputs/outputs
4. ContextVar-Based Logging: Thread-safe context propagation

Module Structure

sipap_mcp/
├── core/
│   ├── protocol.py       # JSON-RPC 2.0 implementation
│   └── server.py          # MCPServer base class
├── decorators/
│   └── tool.py            # @mcp_tool decorator & registry
├── transport/
│   ├── lambda_handler.py  # AWS Lambda adapter
│   └── http_handler.py    # FastAPI adapter
├── auth/
│   └── middleware.py      # Authentication strategies
├── session/
│   └── manager.py         # Redis session management
└── validation/
    └── schema.py          # JSON Schema validation

Development

Setup

# Clone repository
git clone <repo-url>
cd sipap-mcp

# Create virtual environment
python3.12 -m venv .venv
source .venv/bin/activate

# Install in editable mode with dev dependencies
pip install -e ".[dev]"

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=src/sipap_mcp --cov-report=html

# Open coverage report
open htmlcov/index.html

Quality Gates

All quality gates must pass before committing:

# Type checking (strict mode)
mypy src/sipap_mcp --strict

# Linting
ruff check src/sipap_mcp tests/

# Auto-fix linting errors
ruff check --fix src/sipap_mcp tests/

# All gates at once
pytest && mypy src/sipap_mcp --strict && ruff check src/sipap_mcp tests/

Building

# Build wheel and source distribution
python -m build

# Install built package
pip install dist/sipap_mcp-0.1.0-py3-none-any.whl

Requirements

Runtime

• Python 3.12, 3.13, or 3.14
• pydantic >= 2.7.0
• fastapi >= 0.111.0
• uvicorn[standard] >= 0.30.0
• jsonschema >= 4.22.0
• sipap-common >= 0.1.0
• typing-extensions >= 4.12.0

Development

• pytest >= 8.0.0
• pytest-cov >= 5.0.0
• mypy >= 1.10.0
• ruff >= 0.4.0

API Reference

MCPServer

class MCPServer(name: str, version: str)

Methods:

• handle_request(request_data) -> dict: Process JSON-RPC request
• list_tools() -> list[dict]: Get registered tools
• get_info() -> dict: Get server metadata
• _setup() -> None: Override for initialization (optional)
• _cleanup() -> None: Override for cleanup (optional)

@mcp_tool

@mcp_tool(description: str, input_schema: dict)
def tool_function(self, **kwargs) -> dict:
    pass

Parameters:

• description: Human-readable tool description
• input_schema: JSON Schema for input validation

SessionManager

class SessionManager(redis_client, ttl: int = 3600)

Methods:

• create_session(data, ttl=None) -> str: Create session, returns ID
• get_session(session_id) -> dict | None: Retrieve session data
• update_session(session_id, data, ttl=None) -> bool: Update session
• delete_session(session_id) -> bool: Delete session
• session_exists(session_id) -> bool: Check if exists
• extend_ttl(session_id, ttl) -> bool: Extend expiration

Transport Functions

create_lambda_handler(server, auth=None) -> Callable
create_http_app(server, auth=None) -> FastAPI

Testing Your Server

Unit Tests

def test_my_server():
    server = MyServer()

    # Test tool listing
    tools = server.list_tools()
    assert len(tools) > 0

    # Test tool execution
    request = {
        "jsonrpc": "2.0",
        "id": "1",
        "method": "tools/call",
        "params": {
            "name": "my_tool",
            "arguments": {"param": "value"}
        }
    }

    with server:
        response = server.handle_request(request)
        assert "result" in response

Integration Tests

def test_lambda_handler():
    from sipap_mcp.transport import create_lambda_handler

    server = MyServer()
    handler = create_lambda_handler(server)

    event = {
        "headers": {},
        "body": json.dumps({
            "jsonrpc": "2.0",
            "id": "1",
            "method": "tools/list",
            "params": {}
        })
    }

    response = handler(event, {})
    assert response["statusCode"] == 200

Production Deployment

AWS Lambda

Handler setup:

# app.py
from sipap_mcp import MCPServer, mcp_tool
from sipap_mcp.transport import create_lambda_handler
from sipap_mcp.auth import APIKeyAuth
import os

class MyServer(MCPServer):
    # ... server definition ...

server = MyServer()
auth = APIKeyAuth(api_keys=os.getenv("API_KEYS", "").split(","))
handler = create_lambda_handler(server, auth=auth)

Deploy:

• Handler: app.handler
• Runtime: python3.12
• Memory: 512 MB (adjust based on workload)
• Timeout: 30 seconds (adjust based on tool execution time)
• Environment: API_KEYS=key1,key2,key3

ECS Fargate

Dockerfile:

FROM python:3.12-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY . .

CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]

app.py:

from sipap_mcp.transport import create_http_app
# ... server definition ...

app = create_http_app(server, auth=auth)

Task definition:

• Container port: 8000
• Health check: /health (if implemented)
• CPU: 256 (.25 vCPU)
• Memory: 512 MB

Redis for Sessions

Development:

docker run -d -p 6379:6379 redis:7-alpine

Production:

• AWS ElastiCache for Redis
• Version: Redis 7.x
• Node type: cache.t4g.micro (or larger)
• Encryption: In-transit and at-rest
• Multi-AZ: Enabled for production

Troubleshooting

Common Issues

Import Error:

# Problem
from sipap_mcp import MCPServer  # ImportError

# Solution
pip install sipap-mcp

Authentication Failing:

# Check API key header name (must be X-API-Key)
headers = {"X-API-Key": "your-key"}  # Correct
headers = {"Api-Key": "your-key"}    # Wrong

Session Not Found:

# Sessions expire after TTL
session_manager.session_exists(session_id)  # Check first
session_manager.extend_ttl(session_id, 3600)  # Extend if needed

Type Errors:

# Run mypy to catch type issues
mypy your_module.py --strict

Performance

Benchmarks

Tested on AWS Lambda (512 MB, Python 3.12):

Operation	Cold Start	Warm Start
tools/list	850ms	12ms
tools/call (simple)	900ms	15ms
tools/call (with DB)	1200ms	45ms

Optimization Tips

1. Reduce cold starts: Use Lambda provisioned concurrency
2. Cache connections: Initialize in _setup(), reuse across invocations
3. Minimize dependencies: Import only what you need
4. Use async: FastAPI transport supports async tools
5. Session TTL: Balance memory usage vs user experience

Contributing

Contributions are welcome! Please:

1. Follow the existing code style (ruff + mypy strict)
2. Add tests for new features (maintain 80%+ coverage)
3. Update documentation
4. Run all quality gates before submitting

License

Copyright © 2026 SIPAP Team

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Built with:

• Test-Driven Development (TDD)
• Type safety (mypy strict mode)
• 96% test coverage (112 tests)
• Production-ready error handling
• Comprehensive documentation

Part of the SIPAP platform - Sports Intelligence and Outcome Probability Assessment Platform