keycardai-mcp 0.3.0

A Python SDK for Model Context Protocol (MCP) functionality with simplified authentication and authorization

KeyCard AI MCP SDK

A comprehensive Python SDK for Model Context Protocol (MCP) functionality that simplifies authentication and authorization concerns for developers working with AI/LLM integrations.

Installation

pip install keycardai-mcp

Quick Start

from keycardai.mcp import *

# MCP Server with authentication
server = MCPServer(
    name="my-mcp-server",
    version="1.0.0",
    auth_config=MCPAuthConfig(
        oauth_client_id="your_client_id",
        oauth_client_secret="your_client_secret"
    )
)

# Register authenticated resources
@server.resource("user-data")
async def get_user_data(context: MCPContext) -> MCPResource:
    # Automatic token validation and user context
    user = context.authenticated_user
    return MCPResource(
        uri=f"user://{user.id}/data",
        content=await fetch_user_data(user.id)
    )

# MCP Client with token management
client = MCPClient(
    server_url="https://api.example.com/mcp",
    auth=MCPOAuthAuth(
        client_id="client_id",
        client_secret="client_secret"
    )
)

# Access authenticated resources
user_data = await client.get_resource("user-data")

🏗️ Architecture & Features

This SDK provides comprehensive MCP functionality with enterprise-grade security:

Core MCP Components

Component	Module	Description
MCP Server	server.py	Authenticated MCP Server - Host MCP resources with built-in OAuth 2.0 authentication
MCP Client	client.py	Secure MCP Client - Connect to MCP servers with automatic token management
Resource Management	resources.py	Authenticated Resources - Secure resource access with user context
Tool Integration	tools.py	Secure Tools - Execute MCP tools with proper authorization

Authentication & Security

Feature	Module	Description
OAuth 2.0 Integration	auth.py	Token Management - Seamless OAuth integration for MCP operations
Token Validation	validation.py	Security Middleware - Automatic token validation and user context
Scope Management	scopes.py	Permission Control - Fine-grained access control for MCP resources
Session Management	sessions.py	Secure Sessions - Persistent authenticated sessions for MCP clients

MCP Protocol Extensions

Standard	Module	Description
Resource Templates	templates.py	Dynamic Resources - Template-based resource generation with auth context
Prompt Security	prompts.py	Secure Prompts - User-aware prompt templates and execution
Tool Authorization	tools.py	Permission Checks - Role-based access control for MCP tools
Logging & Monitoring	monitoring.py	Security Audit - Comprehensive logging of authenticated operations

Features

• ✅ MCP Protocol Compliance: Full implementation of Model Context Protocol standards
• ✅ OAuth 2.0 Integration: Seamless authentication with industry-standard OAuth flows
• ✅ Type Safe: Full type hints with Pydantic models for all MCP operations
• ✅ Async Support: Native async/await support for all MCP operations
• ✅ Enterprise Security: Token validation, scope management, and audit logging
• ✅ Developer Friendly: Simplified API that abstracts away authentication complexity
• ✅ Production Ready: Battle-tested security patterns and comprehensive error handling

Use Cases

🤖 AI Agent Platforms

# Secure MCP server for AI agents
server = MCPServer(auth_required=True)

@server.tool("execute-query")
async def execute_query(context: MCPContext, query: str) -> dict:
    # Only authenticated users with 'query:execute' scope
    if not context.has_scope("query:execute"):
        raise MCPAuthError("Insufficient permissions")
    
    return await database.execute(query, user=context.user)

🔐 Enterprise LLM Integration

# Corporate LLM with secure resource access
client = MCPClient(
    server_url="https://corp-llm.company.com/mcp",
    auth=MCPOAuthAuth.from_client_credentials(
        client_id="corp-client",
        client_secret="secret",
        scopes=["documents:read", "calendar:read"]
    )
)

# Access corporate resources securely
documents = await client.list_resources("documents")

🌐 Multi-Tenant SaaS

# Tenant-aware MCP resources
@server.resource("tenant-data")
async def get_tenant_data(context: MCPContext) -> MCPResource:
    tenant_id = context.user.tenant_id
    return await fetch_tenant_data(tenant_id, user=context.user)

Security Best Practices

Token Management

• Automatic token refresh and rotation
• Secure token storage with encryption
• Scope-based permission validation
• Session timeout and cleanup

Authentication Flows

• Authorization Code flow for web applications
• Client Credentials flow for service-to-service
• Device Code flow for CLI applications
• PKCE for public clients

Monitoring & Compliance

• Comprehensive audit logging
• Rate limiting and abuse prevention
• GDPR-compliant user data handling
• SOC 2 security controls

Development

This package is part of the KeycardAI Python SDK workspace.

To develop:

# From workspace root
uv sync
uv run --package keycardai-mcp pytest

Examples

See the examples directory for comprehensive examples including:

• Basic MCP server setup
• OAuth integration patterns
• Multi-tenant configurations
• Enterprise deployment guides

License

MIT License - see LICENSE file for details.

Support

• 📖 Documentation
• 🐛 Issue Tracker
• 💬 Community Discussions
• 📧 Support Email