Iot Mcp Servers MCP Server

IoT MCP Servers

MCP (Model Context Protocol) servers for IoT platforms — giving AI agents read access to device registries, digital twins, and telemetry.

Structure

Each server is a standalone directory under this repo — its own pyproject.toml, uv.lock, Dockerfile, and mcp.json example config. No shared library layer: every server is independently runnable and dockerizable.

<server-name>/
├── <server-name>mcpserver.py   # FastMCP server (single file)
├── pyproject.toml              # own dependencies
├── uv.lock
├── Dockerfile
├── mcp.json                    # example MCP client config
└── README.md                   # tools, env vars, setup for this server

Servers

More planned: Azure IoT Hub.

Running a server locally

cd <server-name>
uv sync
uv run <server-name>mcpserver.py

Using with an MCP client

Each server directory has an mcp.json with a ready-to-use client config example (Claude Desktop / VS Code / any MCP client). Copy the relevant block into your client's config, filling in the environment variables described in that server's README.

Design principles

• Read-only by default, writes explicit. Tools default to read/list operations. Any write tool is called out explicitly in that server's README. Create/replace tools default to create-only (overwrite=False) using conditional HTTP headers rather than check-then-set, so the safe path is race-free, not just the default. Delete tools, where a server needs them, require an explicit confirm=True — there is no bulk/cascading delete.
• No vendor lock-in. Connectors target the open protocol/API (e.g. Eclipse Ditto's HTTP API), not a single vendor's proprietary extension of it, so they work against any compatible deployment.
• Tested against the real thing. Each server is verified against a real instance of the target platform (usually via Docker), not just mocks.

License

MIT — see LICENSE.