diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 92fd1320..699664ae 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -89,6 +89,32 @@ jobs:
       - uses: julia-actions/julia-uploadcodecov@latest
         env:
           CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+  extra:
+    name: ${{matrix.test_group.test_type}}-${{ matrix.test_group.label }}-${{ matrix.version }}-${{ matrix.arch }}
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        test_group: [
+          {test_type: 'ext', label: 'mooncake'},
+        ]
+        version:
+          - '1.10'
+          - '1'
+        arch:
+          - x64
+    steps:
+      - uses: actions/checkout@v6
+      - uses: julia-actions/setup-julia@latest
+        with:
+          version: ${{ matrix.version }}
+          arch: ${{ matrix.arch }}
+      - uses: julia-actions/cache@v3
+      - uses: julia-actions/julia-buildpkg@v1
+      - run: julia --code-coverage=user --eval 'include("test/${{ matrix.test_group.test_type }}/${{ matrix.test_group.label }}/${{ matrix.test_group.label }}.jl")'
+      - uses: julia-actions/julia-uploadcodecov@latest
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
   docs:
     name: Documentation
     runs-on: ubuntu-latest
diff --git a/.gitignore b/.gitignore
index 94cabef0..0982401f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,3 +7,4 @@
 /benchmark/*.json
 /benchmark/Manifest.toml
 /docs/Manifest.toml
+/test/ext/**/Manifest.toml
diff --git a/Project.toml b/Project.toml
index ba8ee58d..0c76a8e7 100644
--- a/Project.toml
+++ b/Project.toml
@@ -11,10 +11,12 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [weakdeps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
+Mooncake = "da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [extensions]
 StaticArraysChainRulesCoreExt = "ChainRulesCore"
+StaticArraysMooncakeExt = "Mooncake"
 StaticArraysStatisticsExt = "Statistics"
 
 [compat]
@@ -25,6 +27,7 @@ ChainRulesTestUtils = "1"
 InteractiveUtils = "1"
 JLArrays = "0.1"
 LinearAlgebra = "1.6"
+Mooncake = "0.5.27"
 OffsetArrays = "1"
 PrecompileTools = "1"
 Random = "1.6"
diff --git a/ext/StaticArraysMooncakeExt.jl b/ext/StaticArraysMooncakeExt.jl
new file mode 100644
index 00000000..7be613b3
--- /dev/null
+++ b/ext/StaticArraysMooncakeExt.jl
@@ -0,0 +1,158 @@
+module StaticArraysMooncakeExt
+
+using Mooncake
+using Random: AbstractRNG
+using Base: IEEEFloat
+using StaticArrays: StaticArrays, SArray
+
+using Mooncake: @foldable
+
+import Mooncake:
+    MaybeCache,
+    IncCache,
+    SetToZeroCache,
+    NoFData,
+    NoRData,
+    CoDual,
+    Dual,
+    MinimalCtx,
+    primal,
+    tangent,
+    zero_fcodual,
+    tangent_type,
+    fdata_type,
+    rdata_type,
+    zero_tangent_internal,
+    randn_tangent_internal,
+    set_to_zero_internal!!,
+    increment_internal!!,
+    _add_to_primal_internal,
+    tangent_to_primal_internal!!,
+    primal_to_tangent_internal!!,
+    _dot_internal,
+    _scale_internal,
+    zero_rdata,
+    zero_rdata_from_type,
+    can_produce_zero_rdata_from_type,
+    _verify_rdata_value,
+    __verify_fdata_value,
+    _new_
+
+# Element types treated as differentiable: real and complex IEEE floats.
+const _SElt = Union{IEEEFloat,Complex{<:IEEEFloat}}
+
+# An SArray with a supported element type uses *itself* as its tangent type.
+# It is immutable and stores only by-value scalar data, so its fdata is empty
+# and its rdata carries the full tangent. This mirrors how Mooncake handles
+# `Complex{<:IEEEFloat}` in `src/rules/complex.jl`.
+
+@foldable function tangent_type(::Type{SArray{S,T,N,L}}) where {S,T<:_SElt,N,L}
+    return SArray{S,T,N,L}
+end
+
+@foldable function tangent_type(
+    ::Type{NoFData}, ::Type{SArray{S,T,N,L}}
+) where {S,T<:_SElt,N,L}
+    return SArray{S,T,N,L}
+end
+
+# Non-parametric alias used as a constraint, analogous to `CF` in complex.jl.
+const _SAFloat = SArray{S,T,N,L} where {S,T<:_SElt,N,L}
+
+@foldable fdata_type(::Type{T}) where {T<:_SAFloat} = NoFData
+@foldable rdata_type(::Type{T}) where {T<:_SAFloat} = T
+
+tangent(::NoFData, t::_SAFloat) = t
+
+# Core tangent operations.
+
+zero_tangent_internal(p::_SAFloat, ::MaybeCache) = zero(p)
+
+zero_rdata(p::_SAFloat) = zero(p)
+zero_rdata_from_type(::Type{P}) where {P<:_SAFloat} = zero(P)
+@foldable can_produce_zero_rdata_from_type(::Type{<:_SAFloat}) = true
+
+set_to_zero_internal!!(::SetToZeroCache, p::_SAFloat) = zero(p)
+
+function randn_tangent_internal(
+    rng::AbstractRNG, ::SArray{S,T,N,L}, ::MaybeCache
+) where {S,T<:_SElt,N,L}
+    return SArray{S,T,N,L}(ntuple(_ -> randn(rng, T), Val(L)))
+end
+
+increment_internal!!(::IncCache, t::T, s::T) where {T<:_SAFloat} = t + s
+
+_add_to_primal_internal(::MaybeCache, x::T, t::T, ::Bool) where {T<:_SAFloat} = x + t
+
+tangent_to_primal_internal!!(::T, t::T, ::MaybeCache) where {T<:_SAFloat} = t
+primal_to_tangent_internal!!(::T, x::T, ::MaybeCache) where {T<:_SAFloat} = x
+
+# By-value type, so there is no primal address to record.
+function Mooncake.TestUtils.populate_address_map_internal(
+    m::Mooncake.TestUtils.AddressMap, ::P, ::P
+) where {P<:_SAFloat}
+    return m
+end
+
+# rdata/fdata are validated structurally for non-primitive aggregates; by-value
+# SArrays are leaves like `Complex`, so we short-circuit verification.
+_verify_rdata_value(::P, ::P) where {P<:_SAFloat} = nothing
+__verify_fdata_value(::IdDict{Any,Nothing}, ::P, ::P) where {P<:_SAFloat} = nothing
+
+# Delegate element-wise reductions to the existing tuple handlers, which in
+# turn dispatch to per-element `_dot_internal` / `_scale_internal` (correct for
+# both `IEEEFloat` and `Complex{<:IEEEFloat}` element types).
+function _dot_internal(c::MaybeCache, t::T, s::T) where {T<:_SAFloat}
+    return _dot_internal(c, Tuple(t), Tuple(s))
+end
+
+function _scale_internal(c::MaybeCache, a::Float64, t::T) where {T<:_SAFloat}
+    return T(_scale_internal(c, a, Tuple(t)))
+end
+
+# Rules. `_new_` is already declared a primitive globally
+# (`Tuple{typeof(_new_),Vararg}` in `src/rules/new.jl`), so we only need to
+# add more-specific `frule!!` / `rrule!!` methods for SArray construction.
+# Mooncake's IR normalisation rewrites `SArray(...)` constructor calls to
+# `_new_(SArray{S,T,N,L}, data::NTuple{L,T})`.
+
+function Mooncake.frule!!(
+    ::Dual{typeof(_new_)}, ::Dual{Type{P}}, data::Dual{NTuple{L,T}}
+) where {S,T<:_SElt,N,L,P<:SArray{S,T,N,L}}
+    y = _new_(P, primal(data))
+    dy = _new_(P, tangent(data))
+    return Dual(y, dy)
+end
+
+function Mooncake.rrule!!(
+    ::CoDual{typeof(_new_)}, ::CoDual{Type{P}}, data::CoDual{NTuple{L,T}}
+) where {S,T<:_SElt,N,L,P<:SArray{S,T,N,L}}
+    y = _new_(P, primal(data))
+    _new_SArray_pb(dy::P) = NoRData(), NoRData(), Tuple(dy)
+    return zero_fcodual(y), _new_SArray_pb
+end
+
+Mooncake.@is_primitive MinimalCtx Tuple{
+    typeof(getindex),SArray{S,T,N,L},Int
+} where {S,T<:_SElt,N,L}
+
+function Mooncake.frule!!(
+    ::Dual{typeof(getindex)}, x::Dual{P}, i::Dual{Int}
+) where {S,T<:_SElt,N,L,P<:SArray{S,T,N,L}}
+    idx = primal(i)
+    return Dual(primal(x)[idx], tangent(x)[idx])
+end
+
+function Mooncake.rrule!!(
+    ::CoDual{typeof(getindex)}, x::CoDual{P,NoFData}, i::CoDual{Int}
+) where {S,T<:_SElt,N,L,P<:SArray{S,T,N,L}}
+    idx = primal(i)
+    y = primal(x)[idx]
+    function getindex_SArray_pb(dy::T)
+        dx = P(ntuple(j -> j == idx ? dy : zero(T), Val(L)))
+        return NoRData(), dx, NoRData()
+    end
+    return zero_fcodual(y), getindex_SArray_pb
+end
+
+end # module StaticArraysMooncakeExt
diff --git a/test/ext/mooncake/Project.toml b/test/ext/mooncake/Project.toml
new file mode 100644
index 00000000..68d11901
--- /dev/null
+++ b/test/ext/mooncake/Project.toml
@@ -0,0 +1,11 @@
+[deps]
+AllocCheck = "9b6a8646-10ed-4001-bbdc-1d2f46dfbb1a"
+JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
+Mooncake = "da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
+StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[compat]
+Mooncake = ">=0.5.27"
+StaticArrays = "1"
diff --git a/test/ext/mooncake/mooncake.jl b/test/ext/mooncake/mooncake.jl
new file mode 100644
index 00000000..131edb00
--- /dev/null
+++ b/test/ext/mooncake/mooncake.jl
@@ -0,0 +1,55 @@
+# Run from the repo root with:
+#   julia --project=test/ext/mooncake test/ext/mooncake/mooncake.jl
+
+using Pkg
+Pkg.activate(@__DIR__)
+Pkg.develop(; path=joinpath(@__DIR__, "..", "..", ".."))
+
+using AllocCheck, JET, Mooncake, StableRNGs, StaticArrays, Test
+using Mooncake.TestUtils: test_rule, test_tangent_interface, test_tangent_splitting
+
+# The extension covers `SArray` only by design (it's the by-value, leaf-tangent
+# case); `MArray` falls through to Mooncake's generic mutable-array handling.
+@testset verbose=true "Mooncake integration" begin
+    cases = Any[
+        SVector{3,Float64}(1.0, 2.0, 3.0),
+        SVector{2,Float32}(1.0f0, -2.0f0),
+        SMatrix{2,2,Float64}(1.0, 2.0, 3.0, 4.0),
+        SVector{2,ComplexF64}(1.0 + 2.0im, -3.0 + 1.0im),
+        SVector{1,ComplexF32}(0.5f0 + 0.25f0im),
+    ]
+
+    @testset "tangent interface for $(typeof(p))" for p in cases
+        rng = StableRNG(123)
+        test_tangent_interface(rng, p)
+        test_tangent_splitting(rng, p)
+    end
+
+    @testset "rrule!! getindex $(typeof(p))" for p in cases
+        for i in eachindex(p)
+            test_rule(StableRNG(123), getindex, p, i; is_primitive=true)
+        end
+    end
+
+    @testset "rrule!! _new_ construction" begin
+        # `_new_` is the primitive that IR normalisation lowers `SArray(...)`
+        # construction calls into; test the SArray-specific method directly.
+        new_cases = Any[
+            (SVector{3,Float64}, (1.0, 2.0, 3.0)),
+            (SMatrix{2,2,Float64,4}, (1.0, 2.0, 3.0, 4.0)),
+            (SVector{2,ComplexF64}, (1.0 + 2.0im, -3.0 + 1.0im)),
+        ]
+        for (P, data) in new_cases
+            test_rule(StableRNG(123), Mooncake._new_, P, data; is_primitive=true)
+        end
+    end
+
+    @testset "end-to-end gradient" begin
+        f(x) = x[1]^2 + 2 * x[2] * x[3]
+        x = SVector{3,Float64}(1.5, -2.0, 0.5)
+        cache = Mooncake.prepare_gradient_cache(f, x)
+        val, (_, dx) = Mooncake.value_and_gradient!!(cache, f, x)
+        @test val ≈ f(x)
+        @test dx ≈ SVector{3,Float64}(2 * x[1], 2 * x[3], 2 * x[2])
+    end
+end