nwtools-mcp 0.2.0

MCP server providing IPv4 subnet and address calculation tools

nwtools-mcp

An MCP server that gives LLMs accurate IPv4 subnet and address tools. LLMs are unreliable at network math — this server provides deterministic, correct results via Python's ipaddress standard library.

Tools

Tool	Description
parse_cidr	Network address, broadcast, netmask, wildcard mask, host count
ip_in_subnet	Check whether an IP falls within a subnet
subnets_overlap	Detect overlap between two subnets and return the intersection
cidr_to_range	Convert a CIDR to its first and last IP address
range_to_cidrs	Convert an IP range to the minimal list of covering CIDRs
subtract_subnet	Carve a subnet out of a larger block, returning remaining CIDRs
find_gaps	Find unallocated space within a container block
check_coverage	Check whether a set of CIDRs fully covers a target block
summarize_cidrs	Collapse a list of CIDRs into the minimal set of supernets
classify_ip	Classify an IP as RFC 1918, loopback, link-local, multicast, or public
ip_convert	Convert an IP between dotted-decimal, hex, binary, and integer

Environment variables

Variable	Default	Description
MCP_TRANSPORT	stdio	stdio, streamable-http, or sse
HOST	0.0.0.0	Bind address (HTTP transports only)
PORT	8000	Listen port (HTTP transports only)
API_KEY	(none)	When set, requires X-API-Key: <value> on all HTTP requests
LOG_LEVEL	INFO	Python log level for process and request logging

Local use (stdio)

The stdio transport is used when Claude Desktop spawns the server as a subprocess. No network port is opened.

Run from PyPI with uvx

Once published, the simplest way to run the server locally will be:

uvx nwtools-mcp

That runs the nwtools-mcp console command from an isolated ephemeral environment. For a persistent install:

uv tool install nwtools-mcp
nwtools-mcp

Install and run directly:

pip install -e .
python main.py

Or use the console script:

nwtools-mcp

Or install from PyPI with pip:

pip install nwtools-mcp
nwtools-mcp

Or via Docker:

docker run --rm -i nwtools-mcp

Claude Desktop config

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "nwtools": {
      "command": "python",
      "args": ["/path/to/nwtools-mcp/main.py"]
    }
  }
}

Or with Docker:

{
  "mcpServers": {
    "nwtools": {
      "command": "uvx",
      "args": ["nwtools-mcp"]
    }
  }
}

If you prefer a persistent uv-managed install, use:

{
  "mcpServers": {
    "nwtools": {
      "command": "nwtools-mcp"
    }
  }
}

Remote deployment (HTTP)

The server supports streamable-http (recommended) and sse transports for remote access. Set MCP_TRANSPORT to switch modes.

Running the HTTP server

# Local test
MCP_TRANSPORT=streamable-http python main.py

# With auth
API_KEY=your-secret MCP_TRANSPORT=streamable-http python main.py

With Docker:

docker build -t nwtools-mcp .
docker run --rm -p 8000:8000 \
  -e MCP_TRANSPORT=streamable-http \
  -e API_KEY=your-secret \
  nwtools-mcp

Operational endpoints

When running in HTTP mode, the container exposes two unauthenticated probe endpoints:

Endpoint	Description
/healthz	Basic liveness probe
/readyz	Readiness probe

HTTP requests are also logged as structured JSON lines, including method, path, status, duration, client IP, and request ID.

TLS and auth

The server does not terminate TLS. In production, place it behind a reverse proxy. Example Caddy config:

nwtools.example.com {
    reverse_proxy localhost:8000
}

The built-in API_KEY check adds a layer of defense at the application level, but it does not replace TLS — never expose the server without it.

Connecting Claude to a remote server

In Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "nwtools": {
      "url": "https://nwtools.example.com/mcp",
      "headers": {
        "X-API-Key": "your-secret"
      }
    }
  }
}

On claude.ai, add the server under Settings → Integrations using the same URL.

Development

Install with the test extra and run the suite:

pip install -e ".[test]"
pytest

To build distribution artifacts locally:

uv build

Or with the standard Python build frontend:

pip install build
python -m build

Release

The project is now structured to publish cleanly to PyPI and run via uvx.

Build locally:

uv build

Publish manually with a token:

uv publish

For GitHub Actions, the repo includes publish.yml for PyPI Trusted Publishing. Before using it:

1. Create a pypi environment in the GitHub repository settings.
2. Add a Trusted Publisher for this project on PyPI that matches: Repository owner: crims0n Repository name: nwtools-mcp Workflow filename: publish.yml Environment name: pypi
3. Push a version tag such as v0.2.0.

The publish workflow builds the wheel and sdist, smoke-tests both artifacts, and then runs uv publish.

Requirements

• Python 3.11+
• mcp
• uvicorn