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mindsphere/mindconnect-lib
MindConnect Library (MCL) - Use the MindConnect Library (MCL) to securely connect your on-site device. By cloning or downloading this repository, you accept the Development License Agreement, which you can read by following the link https://developer.mindsphere.io/license.html.
MCL is a C library for connecting embedded and on-premise devices to Siemens' Insights Hub (formerly MindSphere) industrial IoT platform. It handles onboarding, TLS authentication, timeseries data upload, file transfer, and deployment workflows. This is vendor infrastructure code — you'd use it if you're building an IIoT gateway or edge device that needs to talk to Siemens' cloud.
The pluggable architecture for HTTP client, crypto, file I/O, and memory is well thought out — swapping in mbedTLS instead of OpenSSL for a constrained microcontroller is a real use case here and the seams exist to do it cleanly. The library ships with both unit and integration test suites using CMock/Unity, which is more discipline than most embedded C projects bother with. Cross-platform support is genuine: there are build helpers for Linux, Windows, Raspberry Pi, mbedOS, and Sony Spresense, not just token mentions. Component separation (core, connectivity, data lake, deployment) means you can link only what you need, keeping binary size down on constrained targets.
25 stars and 6 forks for an official Siemens library tells you something — this is not a community project, it's a vendor SDK with a GitHub mirror, and the Development License Agreement you're required to accept before cloning makes it non-open in any practical sense. The test suite requires Ruby for code generation, which is an odd dependency for a C embedded project and will break in environments where Ruby isn't available. Documentation lives on the Siemens developer portal, which has a history of requiring login and moving things around, so if that goes away your offline Doxygen build becomes the only reference. There's no package manager support — no vcpkg, no Conan — so integrating this into a modern CMake project means manual dependency wrangling.