NitroStack

A Python-idiomatic port of the NitroStack Model Context Protocol (MCP) framework, enabling NestJS-like modular architecture, dependency injection, execution pipelines, background task processing, built-in authentication modules, and a diagnostic testing harness.

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Features

• Nested Modular Architecture: Group components cleanly with @module.
• Dependency Injection: Explicit class constructor DI with DIContainer and @injectable(deps=[...]).
• Pipeline Interceptors: Build guards, middleware, interceptors, pipes, and exception filters for tool execution.
• Asynchronous Background Tasks: Spawn background workers automatically for long-running tools.
• Built-in Authentication: Modules for API Keys, JWT verification, and OAuth 2.1 (featuring Protected Resource Metadata discovery servers).
• In-Process Testing Harness: Run unit and integration tests against modules without managing subprocesses or real network transports.
• CLI Tooling (nitrostack-py): Scaffold new apps (init), generate boilerplates (generate), auto-register servers with Claude (register), and run hot-reload development servers (dev).

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Installation

pip install nitrostack

To install local developer or test dependencies:

pip install -e .

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Scaffolding a New Project (Recommended)

You can quickly scaffold a new project template using the interactive CLI tool:

nitrostack-py init my-server

(Or via Python: python -m nitrostack.cli.main init my-server)

This launches an interactive prompt where you can:

1. Choose a template:
   • Starter: A simple calculator server.
   • Advanced: A food delivery server with items and order status tracking.
   • OAuth: A flight booking server demonstrating OAuth 2.1 authentication and guarded routes.
2. Provide metadata: Specify a custom description and author name.

Once scaffolded, follow the next steps printed by the CLI to run your server, configure environment variables, and try it out.

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NitroStudio Dashboard

NitroStudio is an interactive visual developer dashboard for inspecting, graphing, and testing your MCP servers.

To launch the dashboard, execute:

nitrostack-studio

If your Python scripts directory is not configured in your system PATH, you can run it via Python:

python -m nitrostack.studio

This launches the interface in your default web browser, allowing you to traverse directories, visualize your dependency graph, test tool execution forms, chat with a local mock LLM, and inspect RPC logs.

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Quick Start

1. Write your First Server

Create a file named app.py:

import asyncio
from pydantic import BaseModel, Field
from nitrostack import (
    tool,
    resource,
    injectable,
    module,
    mcp_app,
    McpApplicationFactory,
    ServerConfig,
    ExecutionContext,
)

# 1. Input Validation Schema
class AddInput(BaseModel):
    a: float = Field(description="First number")
    b: float = Field(description="Second number")

# 2. Injected Provider Service
@injectable(deps=[])
class CalculatorService:
    def add(self, a: float, b: float) -> float:
        return a + b

# 3. Controller
@injectable(deps=[CalculatorService])
class CalculatorController:
    def __init__(self, service: CalculatorService):
        self.service = service

    @tool(
        name="add",
        description="Add two numbers together",
        input_schema=AddInput
    )
    async def add(self, input: AddInput, context: ExecutionContext) -> float:
        context.logger.info(f"Adding {input.a} and {input.b}")
        return self.service.add(input.a, input.b)

    @resource(
        uri="calc://info",
        name="Calculator Info",
        description="Metadata about this calculator"
    )
    async def get_info(self, context: ExecutionContext) -> str:
        return "Simple Add Calculator v1.0.0"

# 4. Modules
@module(
    name="calculator",
    controllers=[CalculatorController],
    providers=[CalculatorService]
)
class CalculatorModule:
    pass

@module(
    name="app",
    imports=[CalculatorModule]
)
class AppModule:
    pass

# 5. Application Entrypoint
@mcp_app(
    module=AppModule,
    server=ServerConfig(name="math-server", version="1.0.0")
)
class App:
    pass

async def main():
    app = await McpApplicationFactory.create(App)
    await app.start()

if __name__ == "__main__":
    asyncio.run(main())

2. Configure Environment Variables

The SDK reads standard settings from the environment or .env files:

Environment Variable	Description
PORT / MCP_SERVER_PORT	The port to bind for HTTP/SSE transport (default: 8000).
MCP_TRANSPORT_TYPE	Transport selection: stdio, http, or dual (combining stdio + HTTP/SSE).
NODE_ENV	If set to production, defaults to dual transport. Otherwise defaults to stdio.
NITROSTACK_LOG_FILE	Destination file for logs (default: nitrostack.log).
NITROSTACK_LOG_LEVEL	Log level (DEBUG, INFO, WARNING, ERROR).
NITROSTACK_LOG_TO_STDOUT	Set to true to allow logging to stdout under stdio transport (Caution: may corrupt protocol stream).

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Developing & Testing

Auto-Registering with Claude Desktop

To automatically configure your server script with Claude Desktop without any manual editing:

nitrostack-py register --name my-mcp-server --file app.py

(If your scripts folder is not in PATH, use: python -m nitrostack.cli.main register --name my-mcp-server --file app.py)

This detects all standard and Windows Store installation directories, sets up virtualenv executables, and writes the JSON configuration. Once registered, simply restart Claude Desktop.

Running Tests

To run the automated test suite, execute:

python tests/test_basic.py
python tests/test_tasks.py
python tests/test_initial_tool.py

Testing Harness

Write in-process unit tests using the harness:

import asyncio
from nitrostack.testing import NitroTestingModule
from app import AppModule

async def test_add():
    harness = await NitroTestingModule.create(AppModule)
    result = await harness.call_tool("add", {"input": {"a": 5, "b": 10}})
    assert result == 15.0
    print("Test passed!")

if __name__ == "__main__":
    asyncio.run(test_add())