diff --git a/MathNet.Numerics.sln b/MathNet.Numerics.sln
index 815226fe..3480c642 100644
--- a/MathNet.Numerics.sln
+++ b/MathNet.Numerics.sln
@@ -50,6 +50,7 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Docs", "Docs", "{039229DA-A
 		docs\content\IntegralTransforms.fsx = docs\content\IntegralTransforms.fsx
 		docs\content\Integration.fsx = docs\content\Integration.fsx
 		docs\content\Interpolation.fsx = docs\content\Interpolation.fsx
+		docs\content\MKL.fsx = docs\content\MKL.fsx
 		docs\content\Random.fsx = docs\content\Random.fsx
 		docs\tools\templates\template.cshtml = docs\tools\templates\template.cshtml
 	EndProjectSection
diff --git a/docs/content/MKL.fsx b/docs/content/MKL.fsx
new file mode 100644
index 00000000..084972cb
--- /dev/null
+++ b/docs/content/MKL.fsx
@@ -0,0 +1,55 @@
+(*** hide ***)
+#I "../../out/lib/net40"
+#r "MathNet.Numerics.dll"
+#r "MathNet.Numerics.FSharp.dll"
+
+(**
+Intel Math Kernel Library (MKL)
+===============================
+
+Math.NET Numerics is designed such that performance-sensitive algorithms
+can be swapped with alternative implementations by the concept of providers.
+There is currently only a provider for linear algebra related routines, but there
+are plans to add additional ones e.g. related to nonlinear optimization problems or signal processing.
+
+Providers become interesting when they can leverage a platform-native high performance library
+like Intel MKL instead of the default purely managed provider. Math.NET Numerics
+provides such a provider in the form of two NuGet packages:
+
+* MathNet.Numerics.MKL.Win-x86
+* MathNet.Numerics.MKL.Win-x64
+
+Equivalent providers for Linux can be built manually from source.
+
+In order to leverage the MKL linear algebra provider, reference the appropriate NuGet package
+in your project. Set "Copy to Output Directory" for both MathNet.Numerics.MKL.dll and libiomp5md.dll
+to "Copy always", or place the two native DLLs manually into the same directory as your application's executable.
+Then enable it by calling:
+
+    [lang=csharp]
+    Control.UseNativeMKL();
+
+Alternatively you can also enable it by setting the environment variable `MathNetNumericsLAProvider=MKL`.
+
+You can also explicitly disable the MKL provider by forcing it to use the managed provider by calling:
+
+    [lang=csharp]
+    Control.UseManaged();
+
+
+Licensing Restrictions
+----------------------
+
+Be aware that unlike the core of Math.NET Numerics including the native wrapper, which are both
+open source under the terms of the MIT/X11 license, the Intel MKL binaries themselves are closed
+source and non-free.
+
+The Math.NET Numerics project does own an Intel MKL license (for Windows, no longer for Linux) and
+thus does have the right to distribute it along Math.NET Numerics. You can therefore use the Math.NET
+Numerics MKL native provider for free for your own use. However, it does *not* give you any right to
+redistribute it again yourself to customers of your own product. **If you need to redistribute,
+buy a license from Intel. If unsure, contact the Intel sales team to clarify.**
+The Math.NET team absolutely loves open source and free access, but we also respect commercial
+vendors and their restricted licensing terms, and ask you to do the same. Thanks.
+
+*)
diff --git a/docs/tools/templates/template.cshtml b/docs/tools/templates/template.cshtml
index 3c3d7c65..5f9377ec 100644
--- a/docs/tools/templates/template.cshtml
+++ b/docs/tools/templates/template.cshtml
@@ -88,12 +88,14 @@
                         <li>Nonlinear Optimization</li>
                         <li><a href="@Root/Distance.html">Distance Metrics</a></li>
 
+                        <li class="nav-header">Native Providers</li>
+                        <li><a href="@Root/MKL.html">Intel MKL</a></li>
+
                         <li class="nav-header">Working Together</li>
                         <li><a href="@Root/CSV.html">Delimited Text Files (CSV)</a></li>
                         <li>NIST MatrixMarket</li>
                         <li>FsLab & Deedle</li>
                         <li>Microsoft Excel</li>
-                        <li>Intel MKL</li>
                         <li>numl.net machine learning</li>
                         <li>MATLAB</li>
                         <li>R-project</li>