mcp-common 0.4.1

ACB-native foundation library providing battle-tested patterns for MCP (Model Context Protocol) servers, with dependency injection, structured logging, and lifecycle management

mcp-common

Version: 0.3.6 (Oneiric-Native) Status: Production Ready

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Overview

mcp-common is an Oneiric-native foundation library for building production-grade MCP (Model Context Protocol) servers. It provides battle-tested patterns extracted from 9 production servers including crackerjack, session-mgmt-mcp, and fastblocks.

🎯 What This Library Provides:

• Oneiric CLI Factory (v0.3.3+) - Standardized server lifecycle with start/stop/restart/status/health commands
• HTTP Client Adapter - Connection pooling with httpx for 11x performance
• Security Utilities - API key validation and input sanitization
• Rich Console UI - Beautiful panels and notifications for server operations
• Settings Management - YAML + environment variable configuration (Pydantic-based)
• Health Check System - Production-ready health monitoring
• Type-Safe - Full Pydantic validation and type hints

Design Principles:

1. Oneiric-Native - Direct Pydantic, Rich library, and standard patterns
2. Production-Ready - Extracted from real production systems
3. Layered Configuration - YAML files + environment variables with clear priority
4. Rich UI - Professional console output with Rich panels
5. Type-safe - Full type hints with strict MyPy checking
6. Well-Tested - 90% coverage minimum

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📚 Examples

See examples/ for complete production-ready examples:

1. CLI Server (Oneiric-Native) - NEW in v0.3.3

Demonstrates the CLI factory for standardized server lifecycle management:

• 5 lifecycle commands (start, stop, restart, status, health)
• PID file management with security validation
• Runtime health snapshots
• Graceful shutdown with signal handling
• Custom lifecycle handlers

cd examples
python cli_server.py start
python cli_server.py status
python cli_server.py health
python cli_server.py stop

2. Weather MCP Server (Oneiric-Native)

Demonstrates HTTP adapters and FastMCP integration:

• HTTPClientAdapter with connection pooling (11x performance)
• MCPBaseSettings with YAML + environment configuration
• ServerPanels for beautiful terminal UI
• Oneiric configuration patterns (direct instantiation)
• FastMCP tool integration (optional; install separately)

cd examples
python weather_server.py

Full documentation: examples/README.md

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Quick Start

Installation

pip install mcp-common>=0.3.6

This automatically installs Pydantic, Rich, and all required dependencies.

If you plan to run an MCP server (e.g., the examples), install a protocol host such as FastMCP separately:

pip install fastmcp
# or
uv add fastmcp

Minimal Example

# my_server/settings.py
from mcp_common.config import MCPBaseSettings
from pydantic import Field


class MyServerSettings(MCPBaseSettings):
    """Server configuration following Oneiric pattern.

    Loads from (priority order):
    1. settings/local.yaml (gitignored)
    2. settings/my-server.yaml
    3. Environment variables MY_SERVER_*
    4. Defaults below
    """

    api_key: str = Field(description="API key for service")
    timeout: int = Field(default=30, description="Request timeout")


# my_server/main.py
from fastmcp import FastMCP  # Optional: install fastmcp separately
from mcp_common import ServerPanels, HTTPClientAdapter, HTTPClientSettings
from my_server.settings import MyServerSettings

# Initialize
mcp = FastMCP("MyServer")
settings = MyServerSettings.load("my-server")

# Initialize HTTP adapter
http_settings = HTTPClientSettings(timeout=settings.timeout)
http_adapter = HTTPClientAdapter(settings=http_settings)


# Define tools
@mcp.tool()
async def call_api():
    # Use the global adapter instance
    response = await http_adapter.get("https://api.example.com")
    return response.json()


# Run server
if __name__ == "__main__":
    # Display startup panel
    ServerPanels.startup_success(
        server_name="My MCP Server",
        version="1.0.0",
        features=["HTTP Client", "YAML Configuration"],
    )

    mcp.run()

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Core Features

🔌 HTTP Client Adapter

Connection Pooling with httpx:

• 11x faster than creating clients per request
• Automatic initialization and cleanup
• Configurable timeouts, retries, connection limits

from mcp_common import HTTPClientAdapter, HTTPClientSettings

# Configure HTTP adapter
http_settings = HTTPClientSettings(
    timeout=30,
    max_connections=50,
    retry_attempts=3,
)

# Create adapter
http_adapter = HTTPClientAdapter(settings=http_settings)

# Make requests
response = await http_adapter.get("https://api.example.com")

Note: Rate limiting is not provided by this library. If you use FastMCP, its built-in RateLimitingMiddleware can be enabled; otherwise, use project-specific configuration.

🎯 Oneiric CLI Factory (NEW in v0.3.3)

Production-Ready Server Lifecycle Management:

The MCPServerCLIFactory provides standardized CLI commands for managing MCP server lifecycles, inspired by Oneiric's operational patterns. It handles process management, health monitoring, and graceful shutdown out of the box.

Features:

• 5 Standard Commands - start, stop, restart, status, health
• Security-First - Secure PID files (0o600), cache directories (0o700), ownership validation
• Process Validation - Detects stale PIDs, prevents race conditions, validates process identity
• Health Monitoring - Runtime health snapshots with configurable TTL
• Signal Handling - Graceful shutdown on SIGTERM/SIGINT
• Custom Handlers - Extensible lifecycle hooks for server-specific logic
• Dual Output - Human-readable and JSON output modes
• Standard Exit Codes - Shell-scriptable with semantic exit codes

Quick Example:

from mcp_common.cli import MCPServerCLIFactory, MCPServerSettings

# 1. Load settings (YAML + env vars)
settings = MCPServerSettings.load("my-server")


# 2. Define lifecycle handlers
def start_server():
    print("Server initialized!")
    # Your server startup logic here


def stop_server(pid: int):
    print(f"Stopping PID {pid}")
    # Your cleanup logic here


def check_health():
    # Return current health snapshot
    return RuntimeHealthSnapshot(
        orchestrator_pid=os.getpid(),
        watchers_running=True,
    )


# 3. Create CLI factory
factory = MCPServerCLIFactory(
    server_name="my-server",
    settings=settings,
    start_handler=start_server,
    stop_handler=stop_server,
    health_probe_handler=check_health,
)

# 4. Create and run Typer app
app = factory.create_app()

if __name__ == "__main__":
    app()

Command Usage:

# Start server (creates PID file and health snapshot)
python my_server.py start

# Check status (lightweight process check)
python my_server.py status
# Output: Server running (PID 12345, snapshot age: 2.3s, fresh: True)

# View health (detailed health information)
python my_server.py health

# Live health probe
python my_server.py health --probe

# Stop server (graceful shutdown with SIGTERM)
python my_server.py stop

# Force stop with timeout
python my_server.py stop --timeout 5 --force

# Restart (stop + start)
python my_server.py restart

# JSON output for automation
python my_server.py status --json

Configuration:

Settings are loaded from multiple sources (priority order):

1. settings/local.yaml (gitignored, for development)
2. settings/{server-name}.yaml (checked into repo)
3. Environment variables MCP_SERVER_*
4. Defaults in MCPServerSettings

Example settings/my-server.yaml:

server_name: "My MCP Server"
cache_root: .oneiric_cache
health_ttl_seconds: 60.0
log_level: INFO

Exit Codes:

• 0 - Success
• 1 - General error
• 2 - Server not running (status/stop)
• 3 - Server already running (start)
• 4 - Health check failed
• 5 - Configuration error
• 6 - Permission error
• 7 - Timeout
• 8 - Stale PID file (use --force)

Full Example:

See examples/cli_server.py for a complete working example with custom commands and health probes.

⚙️ Settings with YAML Support (Oneiric Pattern)

• Pure Pydantic BaseModel
• Layered configuration: YAML files + environment variables
• Type validation with Pydantic
• Path expansion (~ → home directory)

from mcp_common.config import MCPBaseSettings


class ServerSettings(MCPBaseSettings):
    api_key: str  # Required
    timeout: int = 30  # Optional with default


# Load with layered configuration
settings = ServerSettings.load("my-server")
# Loads from:
# 1. settings/my-server.yaml
# 2. settings/local.yaml
# 3. Environment variables MY_SERVER_*
# 4. Defaults

📝 Standard Python Logging

mcp-common uses standard Python logging. Configure as needed for your server:

import logging

# Configure logging
logging.basicConfig(
    level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)

logger = logging.getLogger(__name__)
logger.info("Server started")

🎨 Rich Console UI

• Beautiful startup panels
• Error displays with context
• Statistics tables
• Progress bars

from mcp_common.ui import ServerPanels

ServerPanels.startup_success(
    server_name="Mailgun MCP",
    http_endpoint="http://localhost:8000",
    features=["Rate Limiting", "Security Filters"],
)

🧪 Testing Utilities

• Mock MCP clients
• HTTP response mocking
• Shared fixtures
• DI-friendly testing

from mcp_common.testing import MockMCPClient, mock_http_response


async def test_tool():
    with mock_http_response(status=200, json={"ok": True}):
        result = await my_tool()
    assert result["success"]

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Documentation

• examples/README.md - START HERE - Example servers and usage patterns
• ONEIRIC_CLI_FACTORY_*.md - CLI factory documentation and implementation guides

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Complete Example

See examples/ for a complete production-ready Weather MCP server demonstrating mcp-common patterns.

Key Patterns Demonstrated:

1. Oneiric Settings - YAML + environment variable configuration with .load()
2. HTTP Adapter - HTTPClientAdapter with connection pooling
3. Rich UI - ServerPanels for startup/errors/status
4. Tool Organization - Modular tool registration with FastMCP
5. Configuration Layering - Multiple config sources with clear priority
6. Type Safety - Full Pydantic validation throughout
7. Error Handling - Graceful error display with ServerPanels

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Performance Benchmarks

HTTP Client Adapter (vs new client per request)

Before: 100 requests in 45 seconds, 500MB memory
After:  100 requests in 4 seconds, 50MB memory

Result: 11x faster, 10x less memory

Rate Limiter Overhead

Without: 1000 requests in 1.2 seconds
With:    1000 requests in 1.25 seconds

Result: +4% overhead (negligible vs network I/O)

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Usage Patterns

Pattern 1: Configure Settings with YAML

from mcp_common.config import MCPBaseSettings
from pydantic import Field


class MySettings(MCPBaseSettings):
    api_key: str = Field(description="API key")
    timeout: int = Field(default=30, description="Timeout")


# Load from settings/my-server.yaml + env vars
settings = MySettings.load("my-server")

# Access configuration
print(f"Using API key: {settings.get_masked_key()}")

Pattern 2: Use HTTP Client Adapter

from mcp_common import HTTPClientAdapter, HTTPClientSettings


# Configure HTTP client
http_settings = HTTPClientSettings(
    timeout=30,
    max_connections=50,
    retry_attempts=3,
)

# Create adapter
http = HTTPClientAdapter(settings=http_settings)


# Make requests
@mcp.tool()
async def call_api():
    response = await http.get("https://api.example.com/data")
    return response.json()


# Cleanup when done
await http._cleanup_resources()

Pattern 3: Display Rich UI Panels

from mcp_common import ServerPanels

# Startup panel
ServerPanels.startup_success(
    server_name="My Server",
    version="1.0.0",
    features=["Feature 1", "Feature 2"],
)

# Error panel
ServerPanels.error(
    title="API Error",
    message="Failed to connect",
    suggestion="Check your API key",
)

# Status table
ServerPanels.status_table(
    title="Health Check",
    rows=[
        ("API", "✅ Healthy", "200 OK"),
        ("Database", "⚠️ Degraded", "Slow queries"),
    ],
)

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Development

Setup

git clone https://github.com/lesaker/mcp-common.git
cd mcp-common
pip install -e ".[dev]"

Running Tests

# Run all tests with coverage
pytest --cov=mcp_common --cov-report=html

# Run specific test
pytest tests/test_http_adapter.py -v

# Run with ACB integration tests
pytest tests/integration/ -v

Code Quality

# Format code
ruff format

# Lint code
ruff check

# Type checking
mypy mcp_common tests

# Run all quality checks
crackerjack --all

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Versioning

Recent Versions:

• 0.3.6 - Oneiric-native (removed ACB dependency)
• 0.3.3 - Added Oneiric CLI Factory
• 0.3.0 - Initial Oneiric patterns
• 2.0.0 - Previous ACB-native version (deprecated)

Compatibility:

• Requires Python 3.13+
• Optional: compatible with FastMCP 2.0+
• Uses Pydantic 2.12+, Rich 14.2+

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Success Metrics

Current Status:

1. ✅ Professional Rich UI in all components
2. ✅ 90%+ test coverage maintained
3. ✅ Zero production incidents
4. ✅ Oneiric-native patterns throughout
5. ✅ Standardized CLI lifecycle management
6. ✅ Clean dependency tree (no framework lock-in)

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License

BSD-3-Clause License - See LICENSE for details

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Contributing

Contributions are welcome! Please:

1. Read examples/README.md for usage patterns
2. Follow Oneiric patterns (see examples)
3. Fork and create feature branch
4. Add tests (coverage ≥90%)
5. Ensure all quality checks pass (ruff format && ruff check && mypy && pytest)
6. Submit pull request

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Acknowledgments

Built with patterns extracted from 9 production MCP servers:

Primary Pattern Sources:

• crackerjack - MCP server structure, Rich UI panels, CLI patterns
• session-mgmt-mcp - Configuration patterns, health checks
• fastblocks - Adapter organization, settings management

Additional Contributors:

• raindropio-mcp (HTTP client patterns)
• excalidraw-mcp (testing patterns)
• opera-cloud-mcp
• mailgun-mcp
• unifi-mcp

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Support

For support, please check the documentation in the docs/ directory or create an issue in the repository.

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Ready to get started? Check out examples/ for working examples demonstrating all features!