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    North Mcp Python Sdk

    An sdk for creating MCP Servers with north

    7 stars
    Python
    Updated Nov 3, 2025

    Table of Contents

    • Installation
    • Why this repository
    • Main differences
    • Health Check
    • Examples
    • Authentication
    • I only want north to be able to send requests to my server
    • I want to get the identity of the north user that is calling my server
    • I need access to a third party service via oauth (e.g.: google drive, slack, etc...)
    • Debug Mode
    • Enabling Debug Mode
    • 1. Environment Variable (Recommended)
    • 2. Constructor Parameter
    • What Gets Logged in Debug Mode
    • Example Debug Output
    • Debug Mode Examples
    • Security Note
    • OpenTelemetry
    • What the SDK provides
    • Setup
    • TelemetryConfig options
    • Local Development without North
    • Adding authentication
    • Development
    • Prerequisites
    • Setup
    • Code Formatting
    • Running Tests
    • Contributing

    Table of Contents

    • Installation
    • Why this repository
    • Main differences
    • Health Check
    • Examples
    • Authentication
    • I only want north to be able to send requests to my server
    • I want to get the identity of the north user that is calling my server
    • I need access to a third party service via oauth (e.g.: google drive, slack, etc...)
    • Debug Mode
    • Enabling Debug Mode
    • 1. Environment Variable (Recommended)
    • 2. Constructor Parameter
    • What Gets Logged in Debug Mode
    • Example Debug Output
    • Debug Mode Examples
    • Security Note
    • OpenTelemetry
    • What the SDK provides
    • Setup
    • TelemetryConfig options
    • Local Development without North
    • Adding authentication
    • Development
    • Prerequisites
    • Setup
    • Code Formatting
    • Running Tests
    • Contributing

    Documentation

    North MCP Python SDK

    This SDK builds on top of the original SDK. Please refer to the original repository's README for general information. This README focuses on North-specific details.

    Installation

    code
    uv pip install git+ssh://git@github.com/cohere-ai/north-mcp-python-sdk.git

    Why this repository

    This repository provides code to enable your server to use authentication with North, a custom extension to the original specification. Other than that, no changes are made to the SDK; this builds on top of it.

    Main differences

    • North only supports the StreamableHTTP transport. The sse transport is deprecated, it will work for backwards compatibility, but you shouldn't use it if you are creating new servers
    • You can protect all requests to your server with a secret.
    • You can access the user's OAuth token to interact with third-party services on their behalf.
    • You can access the user's identity (from the identity provider used with North).
    • Debug mode for detailed authentication logging and troubleshooting.
    • OpenTelemetry helpers for custom spans, log/trace correlation, and privacy-aware error recording (built on FastMCP telemetry).
    • Built-in health check endpoint for Kubernetes liveness probes (enabled by default).

    Health Check

    NorthMCPServer includes a built-in /health endpoint that responds to GET requests with a 200 OK plain-text response. This is useful for Kubernetes liveness/readiness probes and load balancer health checks. The endpoint bypasses authentication, so no tokens are needed.

    It is enabled by default. To disable it:

    python
    mcp = NorthMCPServer(name="Demo", health_check=False)

    Examples

    This repository contains example servers that you can use as a quickstart. You can find them in the examples directory.

    Examples cover authentication, tool metadata for the North UI, debug mode, and OpenTelemetry (examples/telemetry-demo/).

    Authentication

    This SDK offers several strategies for authenticating users and authorizing their requests.

    I only want north to be able to send requests to my server

    python
    mcp = NorthMCPServer(name="Demo", port=5222, server_secret="secret")

    I want to get the identity of the north user that is calling my server

    Refer to examples/server_with_auth.py. During your request call the following:

    python
    user = get_authenticated_user()
    print(user.email)

    I need access to a third party service via oauth (e.g.: google drive, slack, etc...)

    Similar as above:

    code
    user = get_authenticated_user()
    print(user.connector_access_tokens)

    Debug Mode

    The North MCP SDK includes a comprehensive debug mode that provides detailed logging of authentication processes, incoming requests, and token validation. This is invaluable when troubleshooting authentication issues.

    Enabling Debug Mode

    There are several ways to enable debug mode:

    1. Environment Variable (Recommended)

    bash
    export DEBUG=true
    python your_server.py

    2. Constructor Parameter

    python
    mcp = NorthMCPServer(name="Demo", port=5222, debug=True)

    What Gets Logged in Debug Mode

    When debug mode is enabled, you'll see detailed logs including:

    • Request Headers: All incoming HTTP headers (including Authorization)
    • Token Parsing: Base64 decoding and JSON parsing of auth tokens
    • JWT Validation: User ID token decoding and validation steps
    • Authentication Details: User email, available connectors, token counts
    • Error Context: Detailed error messages with troubleshooting context

    Example Debug Output

    code
    2024-01-15 10:30:45 - NorthMCP.Auth - DEBUG - Authenticating request from ('127.0.0.1', 54321)
    2024-01-15 10:30:45 - NorthMCP.Auth - DEBUG - Request headers: {'authorization': 'Bearer eyJ...', 'content-type': 'application/json'}
    2024-01-15 10:30:45 - NorthMCP.Auth - DEBUG - Authorization header present (length: 248)
    2024-01-15 10:30:45 - NorthMCP.Auth - DEBUG - Successfully decoded base64 auth header
    2024-01-15 10:30:45 - NorthMCP.Auth - DEBUG - Successfully parsed auth tokens. Has server_secret: True, Has user_id_token: True, Connector count: 2
    2024-01-15 10:30:45 - NorthMCP.Auth - DEBUG - Available connectors: ['google', 'slack']
    2024-01-15 10:30:45 - NorthMCP.Auth - DEBUG - Successfully decoded user ID token. Email: user@example.com
    2024-01-15 10:30:45 - NorthMCP.AuthContext - DEBUG - Setting authenticated user in context: email=user@example.com, connectors=['google', 'slack']

    Debug Mode Examples

    See examples/server_with_debug.py for a runnable example.

    Security Note

    Debug mode logs sensitive information including request headers and token metadata. Never enable debug mode in production environments as it may expose authentication details in logs.

    OpenTelemetry

    FastMCP 3 emits a span for each tool call when a TracerProvider is configured. The North SDK adds helpers on top of that; it does not install exporters or configure where traces are sent — opentelemetry-sdk and OTLP exporters are not bundled dependencies. Servers run fine without a TracerProvider; traces become no-ops until you add one.

    What the SDK provides

    HelperPurpose
    TelemetryConfigOpt-in config object for the telemetry integration (sensitive-data policy, log/trace correlation)
    mcp.telemetry.traced_spanCustom spans nested under FastMCP tool spans, driven by the server's TelemetryConfig. Use this when you have mcp in scope.
    traced_span (module-level)Same context manager, but auto-resolves the active server's config via fastmcp.server.dependencies.get_server. Use this from tool bodies that don't hold an mcp reference.
    get_telemetry_config()Returns the active NorthMCPServer's TelemetryConfig (or a private "off" config when there's no active North server). Lets tools branch on record_sensitive_data without an mcp reference.
    DependsRe-export of FastMCP's Depends factory. Combine with get_telemetry_config for FastAPI-style parameter injection: telemetry: TelemetryConfig = Depends(get_telemetry_config).
    get_tracerRe-export of FastMCP's tracer (fastmcp instrumentation name)
    TraceContextFormatterAppends trace_id / span_id to log lines on the NorthMCP.{name} logger when a span is active

    Setup

    1. **Register a TracerProvider and exporters in main before importing NorthMCPServer** (FastMCP reads the global provider at import time). Use your own setup or standard OTel env vars (OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_SERVICE_NAME, etc.).

    2. **Pass a TelemetryConfig to NorthMCPServer** — this is the opt-in signal. When log_trace_context is enabled (the default for an opted-in config), trace/span IDs are appended automatically to NorthMCP.* log lines.

    3. **Inject the config into tools with Depends(get_telemetry_config)** and call telemetry.traced_span(...) for custom spans. See the helper table for mcp.telemetry and bare-import alternatives.

    python
    def configure_tracing() -> None:
        # Install opentelemetry-sdk + exporters in your server project.
        # See examples/telemetry-demo/main.py for a minimal OTLP gRPC example.
        ...
    
    def main() -> None:
        configure_tracing()
    
        from north_mcp_python_sdk import (
            Depends,
            NorthMCPServer,
            TelemetryConfig,
            get_telemetry_config,
        )
    
        mcp = NorthMCPServer(
            "Search",
            telemetry=TelemetryConfig(
                record_sensitive_data=False,
                log_trace_context=True,
            ),
        )
    
        @mcp.tool()
        async def search(
            query: str,
            telemetry: TelemetryConfig = Depends(get_telemetry_config),
        ) -> list[dict]:
            # FastMCP injects the active server's TelemetryConfig as `telemetry`
            # before the tool body runs. No reference to `mcp` is needed, and
            # `telemetry.traced_span` honours `record_sensitive_data` for
            # exception details.
            with telemetry.traced_span(
                "search.provider_call",
                attributes={"search.query_length": len(query)},
            ) as span:
                if telemetry.record_sensitive_data:
                    span.add_event("search.query", {"query": query})
    
                results = await provider.search(query)
                span.set_attribute("search.result_count", len(results))
                return results

    Depends(...) in a default trips ruff's B008 and basedpyright's reportCallInDefaultInitializer. Whitelist Depends as configured in this repo's pyproject.toml; this is the same approach FastAPI projects use.

    Full walkthrough: [examples/telemetry-demo/main.py](examples/telemetry-demo/main.py). For broader auto-instrumentation (HTTP, logging, etc.), use the [opentelemetry-instrument](https://opentelemetry.io/docs/zero-code/python/) CLI per FastMCP telemetry docs.

    TelemetryConfig options

    OptionDefault (when opted in)Description
    record_sensitive_dataFalseWhen True, traced_span records full exception messages on spans and tools may attach sensitive payloads (query text, IDs, etc.) as span events. Off by default for safety; opt in explicitly in code only.
    log_trace_contextTrueWhen True, the SDK attaches a formatter that appends trace_id / span_id to log lines on the NorthMCP.* logger while a span is active.

    If you leave telemetry=None, the SDK uses an internal "telemetry not opted in" config: both flags False, no formatter is attached to the NorthMCP.* logger, and traced_span records only the exception type name on error. Neither flag has an environment-variable fallback. FastMCP's own tool/resource/prompt spans are unaffected — they still appear whenever a TracerProvider is configured.

    python
    mcp = NorthMCPServer(
        name="Demo",
        telemetry=TelemetryConfig(record_sensitive_data=True),
    )

    Local Development without North

    This guide describes how to test your MCP server locally without connecting it to North. For this, we will use the MCP Inspector. You can run it with:

    code
    npx @modelcontextprotocol/inspector

    If authentication is not required and you just want to run it locally, you can choose the stdio transport. Navigate to the MCP Inspector and configure it as follows:

    • Transport Type: stdio
    • Command: uv
    • Arguments: run examples/server_with_auth.py --transport stdio

    From here:

    • Click "Connect"
    • Select "Tools" on the top of the screen.
    • Click "List Tools" -> "add"
    • Add the numbers and click "Run". You should see the sum.

    Adding authentication

    If you want to test the authentication mechanism locally you can do the following. First start the server with the streamable http transport:

    code
    uv run examples/server_with_auth.py --transport streamable-http

    Next, create a bearer token. You can generate one using examples/create_bearer_token.py or use a pre-made one.

    Navigate to the MCP Inspector and configure it like this:

    • Transport Type: Streamable HTTP
    • URL: http://localhost:5222/mcp
    • Authentication -> Bearer token: eyJzZXJ2ZXJfc2VjcmV0IjogInNlcnZlcl9zZWNyZXQiLCAidXNlcl9pZF90b2tlbiI6ICJleUpoYkdjaU9pSklVekkxTmlJc0luUjVjQ0k2SWtwWFZDSjkuZXlKbGJXRnBiQ0k2SW5SbGMzUkFZMjl0Y0dGdWVTNWpiMjBpZlEuV0pjckVUUi1MZnFtX2xrdE9vdjd0Q1ktTmZYR2JuYTVUMjhaeFhTaEZ4SSIsICJjb25uZWN0b3JfYWNjZXNzX3Rva2VucyI6IHsiZ29vZ2xlIjogImFiYyJ9fQ==

    Follow the same process as before. When you call the tool, you should see the following log in the terminal where you started the server:

    code
    This tool was called by: test@company.com

    Development

    Prerequisites

    To contribute to this project, you'll need:

    • Python 3.11+: Required for the SDK
    • uv >= 0.8.13: Used for dependency management, formatting, and CI checks

    Setup

    1. Clone the repository:

    bash
    git clone https://github.com/cohere-ai/north-mcp-python-sdk.git
       cd north-mcp-python-sdk

    2. Install dependencies:

    bash
    uv sync --dev

    Code Formatting

    This project uses uv format for consistent code formatting. The CI pipeline enforces these standards:

    bash
    # Check formatting (same as CI)
    uv format --preview-features format --check
    
    # Apply formatting
    uv format --preview-features format

    Running Tests

    bash
    uv run pytest

    Contributing

    Before submitting a PR:

    1. Ensure your code passes formatting checks: uv format --preview-features format --check

    2. Run the test suite: uv run pytest

    3. Follow the existing code style and patterns

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