diff --git a/README.md b/README.md
index 1368a61b..2d118a28 100644
--- a/README.md
+++ b/README.md
@@ -84,40 +84,46 @@ The complete list of methods that an interface may implement can be found in the
 
 `NLPModelMeta` objects have the following attributes (with `S <: AbstractVector`):
 
-Attribute   | Type               | Notes
-------------|--------------------|------------------------------------
-`nvar`      | `Int             ` | number of variables
-`x0  `      | `S`                | initial guess
-`lvar`      | `S`                | vector of lower bounds
-`uvar`      | `S`                | vector of upper bounds
-`ifix`      | `Vector{Int}`      | indices of fixed variables
-`ilow`      | `Vector{Int}`      | indices of variables with lower bound only
-`iupp`      | `Vector{Int}`      | indices of variables with upper bound only
-`irng`      | `Vector{Int}`      | indices of variables with lower and upper bound (range)
-`ifree`     | `Vector{Int}`      | indices of free variables
-`iinf`      | `Vector{Int}`      | indices of visibly infeasible bounds
-`ncon`      | `Int             ` | total number of general constraints
-`nlin `     | `Int             ` | number of linear constraints
-`nnln`      | `Int             ` | number of nonlinear general constraints
-`y0  `      | `S`                | initial Lagrange multipliers
-`lcon`      | `S`                | vector of constraint lower bounds
-`ucon`      | `S`                | vector of constraint upper bounds
-`lin `      | `Vector{Int}`      | indices of linear constraints
-`nln`       | `Vector{Int}`      | indices of nonlinear constraints
-`jfix`      | `Vector{Int}`      | indices of equality constraints
-`jlow`      | `Vector{Int}`      | indices of constraints of the form c(x) ≥ cl
-`jupp`      | `Vector{Int}`      | indices of constraints of the form c(x) ≤ cu
-`jrng`      | `Vector{Int}`      | indices of constraints of the form cl ≤ c(x) ≤ cu
-`jfree`     | `Vector{Int}`      | indices of "free" constraints (there shouldn't be any)
-`jinf`      | `Vector{Int}`      | indices of the visibly infeasible constraints
-`nnzo`      | `Int             ` | number of nonzeros in the gradient
-`nnzh`      | `Int             ` | number of nonzeros in the sparse Hessian
-`nnzj`      | `Int             ` | number of nonzeros in the sparse Jacobian
-`lin_nnzj`  | `Int             ` | number of nonzeros in the linear part of sparse Jacobian
-`nln_nnzj`  | `Int             ` | number of nonzeros in the nonlinear part of sparse Jacobian
-`minimize`  | `Bool            ` | true if `optimize == minimize`
-`islp`      | `Bool            ` | true if the problem is a linear program
-`name`      | `String`           | problem name
+Attribute            | Type          | Notes
+---------------------|---------------|------------------------------------
+`nvar`               | `Int`         | number of variables
+`x0  `               | `S`           | initial guess
+`lvar`               | `S`           | vector of lower bounds
+`uvar`               | `S`           | vector of upper bounds
+`ifix`               | `Vector{Int}` | indices of fixed variables
+`ilow`               | `Vector{Int}` | indices of variables with lower bound only
+`iupp`               | `Vector{Int}` | indices of variables with upper bound only
+`irng`               | `Vector{Int}` | indices of variables with lower and upper bound (range)
+`ifree`              | `Vector{Int}` | indices of free variables
+`iinf`               | `Vector{Int}` | indices of visibly infeasible bounds
+`ncon`               | `Int`         | total number of general constraints
+`nlin `              | `Int`         | number of linear constraints
+`nnln`               | `Int`         | number of nonlinear general constraints
+`y0  `               | `S`           | initial Lagrange multipliers
+`lcon`               | `S`           | vector of constraint lower bounds
+`ucon`               | `S`           | vector of constraint upper bounds
+`lin `               | `Vector{Int}` | indices of linear constraints
+`nln`                | `Vector{Int}` | indices of nonlinear constraints
+`jfix`               | `Vector{Int}` | indices of equality constraints
+`jlow`               | `Vector{Int}` | indices of constraints of the form c(x) ≥ cl
+`jupp`               | `Vector{Int}` | indices of constraints of the form c(x) ≤ cu
+`jrng`               | `Vector{Int}` | indices of constraints of the form cl ≤ c(x) ≤ cu
+`jfree`              | `Vector{Int}` | indices of "free" constraints (there shouldn't be any)
+`jinf`               | `Vector{Int}` | indices of the visibly infeasible constraints
+`nnzo`               | `Int`         | number of nonzeros in the gradient
+`nnzj`               | `Int`         | number of nonzeros in the sparse Jacobian
+`lin_nnzj`           | `Int`         | number of nonzeros in the sparse linear constraints Jacobian
+`nln_nnzj`           | `Int`         | number of nonzeros in the sparse nonlinear constraints Jacobian
+`nnzh`               | `Int`         | number of nonzeros in the lower triangular part of the sparse Hessian of the Lagrangian
+`minimize`           | `Bool`        | true if `optimize == minimize`
+`islp`               | `Bool`        | true if the problem is a linear program
+`name`               | `String`      | problem name
+`gradient_available` | `Bool`        | true if the gradient of the objective is available
+`jacobian_available` | `Bool`        | true if the sparse Jacobian of the constraints is available
+`hessian_available`  | `Bool`        | true if the sparse Hessian of the Lagrangian is available
+`Jv_available`       | `Bool`        | true if the Jacobian-vector product `J * v` is available
+`Jtv_available`      | `Bool`        | true if the transpose Jacobian-vector product `J' * v` is available
+`Hv_available`       | `Bool`        | true if the Hessian-vector product of the Lagrangian `H * v` is available
 
 # Bug reports and discussions
 
diff --git a/docs/src/index.md b/docs/src/index.md
index 7f5b1bcf..70bfe679 100644
--- a/docs/src/index.md
+++ b/docs/src/index.md
@@ -79,40 +79,46 @@ See the [Models](@ref), the [Tools](@ref tools-section), or the [API](@ref).
 
 `NLPModelMeta` objects have the following attributes (with `S <: AbstractVector`):
 
-Attribute   | Type               | Notes
-------------|--------------------|------------------------------------
-`nvar`      | `Int             ` | number of variables
-`x0  `      | `S`                | initial guess
-`lvar`      | `S`                | vector of lower bounds
-`uvar`      | `S`                | vector of upper bounds
-`ifix`      | `Vector{Int}`      | indices of fixed variables
-`ilow`      | `Vector{Int}`      | indices of variables with lower bound only
-`iupp`      | `Vector{Int}`      | indices of variables with upper bound only
-`irng`      | `Vector{Int}`      | indices of variables with lower and upper bound (range)
-`ifree`     | `Vector{Int}`      | indices of free variables
-`iinf`      | `Vector{Int}`      | indices of visibly infeasible bounds
-`ncon`      | `Int             ` | total number of general constraints
-`nlin `     | `Int             ` | number of linear constraints
-`nnln`      | `Int             ` | number of nonlinear general constraints
-`y0  `      | `S`                | initial Lagrange multipliers
-`lcon`      | `S`                | vector of constraint lower bounds
-`ucon`      | `S`                | vector of constraint upper bounds
-`lin `      | `Vector{Int}`      | indices of linear constraints
-`nln`       | `Vector{Int}`      | indices of nonlinear constraints
-`jfix`      | `Vector{Int}`      | indices of equality constraints
-`jlow`      | `Vector{Int}`      | indices of constraints of the form c(x) ≥ cl
-`jupp`      | `Vector{Int}`      | indices of constraints of the form c(x) ≤ cu
-`jrng`      | `Vector{Int}`      | indices of constraints of the form cl ≤ c(x) ≤ cu
-`jfree`     | `Vector{Int}`      | indices of "free" constraints (there shouldn't be any)
-`jinf`      | `Vector{Int}`      | indices of the visibly infeasible constraints
-`nnzo`      | `Int             ` | number of nonzeros in the gradient
-`nnzj`      | `Int             ` | number of nonzeros in the sparse Jacobian
-`lin_nnzj`  | `Int             ` | number of nonzeros in the sparse linear constraints Jacobian
-`nln_nnzj`  | `Int             ` | number of nonzeros in the sparse nonlinear constraints Jacobian
-`nnzh`      | `Int             ` | number of nonzeros in the lower triangular part of the sparse Hessian of the Lagrangian
-`minimize`  | `Bool            ` | true if `optimize == minimize`
-`islp`      | `Bool            ` | true if the problem is a linear program
-`name`      | `String`           | problem name
+Attribute            | Type          | Notes
+---------------------|---------------|------------------------------------
+`nvar`               | `Int`         | number of variables
+`x0  `               | `S`           | initial guess
+`lvar`               | `S`           | vector of lower bounds
+`uvar`               | `S`           | vector of upper bounds
+`ifix`               | `Vector{Int}` | indices of fixed variables
+`ilow`               | `Vector{Int}` | indices of variables with lower bound only
+`iupp`               | `Vector{Int}` | indices of variables with upper bound only
+`irng`               | `Vector{Int}` | indices of variables with lower and upper bound (range)
+`ifree`              | `Vector{Int}` | indices of free variables
+`iinf`               | `Vector{Int}` | indices of visibly infeasible bounds
+`ncon`               | `Int`         | total number of general constraints
+`nlin `              | `Int`         | number of linear constraints
+`nnln`               | `Int`         | number of nonlinear general constraints
+`y0  `               | `S`           | initial Lagrange multipliers
+`lcon`               | `S`           | vector of constraint lower bounds
+`ucon`               | `S`           | vector of constraint upper bounds
+`lin `               | `Vector{Int}` | indices of linear constraints
+`nln`                | `Vector{Int}` | indices of nonlinear constraints
+`jfix`               | `Vector{Int}` | indices of equality constraints
+`jlow`               | `Vector{Int}` | indices of constraints of the form c(x) ≥ cl
+`jupp`               | `Vector{Int}` | indices of constraints of the form c(x) ≤ cu
+`jrng`               | `Vector{Int}` | indices of constraints of the form cl ≤ c(x) ≤ cu
+`jfree`              | `Vector{Int}` | indices of "free" constraints (there shouldn't be any)
+`jinf`               | `Vector{Int}` | indices of the visibly infeasible constraints
+`nnzo`               | `Int`         | number of nonzeros in the gradient
+`nnzj`               | `Int`         | number of nonzeros in the sparse Jacobian
+`lin_nnzj`           | `Int`         | number of nonzeros in the sparse linear constraints Jacobian
+`nln_nnzj`           | `Int`         | number of nonzeros in the sparse nonlinear constraints Jacobian
+`nnzh`               | `Int`         | number of nonzeros in the lower triangular part of the sparse Hessian of the Lagrangian
+`minimize`           | `Bool`        | true if `optimize == minimize`
+`islp`               | `Bool`        | true if the problem is a linear program
+`name`               | `String`      | problem name
+`gradient_available` | `Bool`        | true if the gradient of the objective is available
+`jacobian_available` | `Bool`        | true if the sparse Jacobian of the constraints is available
+`hessian_available`  | `Bool`        | true if the sparse Hessian of the Lagrangian is available
+`Jv_available`       | `Bool`        | true if the Jacobian-vector product `J * v` is available
+`Jtv_available`      | `Bool`        | true if the transpose Jacobian-vector product `J' * v` is available
+`Hv_available`       | `Bool`        | true if the Hessian-vector product of the Lagrangian `H * v` is available
 
 ## License
 
diff --git a/src/nlp/meta.jl b/src/nlp/meta.jl
index ab3d0ea4..1232fdfd 100644
--- a/src/nlp/meta.jl
+++ b/src/nlp/meta.jl
@@ -51,6 +51,12 @@ The following keyword arguments are accepted:
 - `minimize`: true if optimize == minimize
 - `islp`: true if the problem is a linear program
 - `name`: problem name
+- `gradient_available`: indicates whether the gradient of the objective is available
+- `jacobian_available`: indicates whether the sparse Jacobian of the constraints is available
+- `hessian_available`: indicates whether the sparse Hessian of the Lagrangian is available
+- `Jv_available`: indicates whether the Jacobian-vector product `J * v` is available
+- `Jtv_available`: indicates whether the transpose Jacobian-vector product `J' * v` is available
+- `Hv_available`: indicates whether the Hessian-vector product of the Lagrangian `H * v` is available
 
 `NLPModelMeta` also contains the following attributes, which are computed from the variables above:
 - `nvar`: number of variables
@@ -114,6 +120,13 @@ struct NLPModelMeta{T, S} <: AbstractNLPModelMeta{T, S}
   minimize::Bool
   islp::Bool
   name::String
+
+  gradient_available::Bool
+  jacobian_available::Bool
+  hessian_available::Bool
+  Jv_available::Bool
+  Jtv_available::Bool
+  Hv_available::Bool
 end
 
 function NLPModelMeta{T, S}(
@@ -134,9 +147,15 @@ function NLPModelMeta{T, S}(
   nln_nnzj = nnzj - lin_nnzj,
   nnzh = nvar * (nvar + 1) / 2,
   lin = Int[],
-  minimize = true,
-  islp = false,
+  minimize::Bool = true,
+  islp::Bool = false,
   name = "Generic",
+  gradient_available::Bool = true,
+  jacobian_available::Bool = true,
+  hessian_available::Bool = true,
+  Jv_available::Bool = true,
+  Jtv_available::Bool = true,
+  Hv_available::Bool = true,
 ) where {T, S}
   if (nvar < 1) || (ncon < 0)
     error("Nonsensical dimensions")
@@ -213,6 +232,12 @@ function NLPModelMeta{T, S}(
     minimize,
     islp,
     name,
+    gradient_available,
+    jacobian_available,
+    hessian_available,
+    Jv_available,
+    Jtv_available,
+    Hv_available,
   )
 end
 
@@ -238,9 +263,15 @@ function NLPModelMeta(
   nln_nnzj = meta.nln_nnzj,
   nnzh = meta.nnzh,
   lin = meta.lin,
-  minimize = meta.minimize,
-  islp = meta.islp,
+  minimize::Bool = meta.minimize,
+  islp::Bool = meta.islp,
   name = meta.name,
+  gradient_available::Bool = meta.gradient_available,
+  jacobian_available::Bool = meta.jacobian_available,
+  hessian_available::Bool = meta.hessian_available,
+  Jv_available::Bool = meta.Jv_available,
+  Jtv_available::Bool = meta.Jtv_available,
+  Hv_available::Bool = meta.Hv_available,
 ) where {T, S}
   NLPModelMeta{T, S}(
     nvar,
@@ -263,6 +294,12 @@ function NLPModelMeta(
     minimize = minimize,
     islp = islp,
     name = name,
+    gradient_available = gradient_available,
+    jacobian_available = jacobian_available,
+    hessian_available = hessian_available,
+    Jv_available = Jv_available,
+    Jtv_available = Jtv_available,
+    Hv_available = Hv_available,
   )
 end
 
diff --git a/src/nls/meta.jl b/src/nls/meta.jl
index 5862cc09..fc9276e7 100644
--- a/src/nls/meta.jl
+++ b/src/nls/meta.jl
@@ -15,6 +15,11 @@ The following keyword arguments are accepted:
 - `nnzj`: number of elements needed to store the nonzeros of the Jacobian of the residual
 - `nnzh`: number of elements needed to store the nonzeros of the sum of Hessians of the residuals
 - `lin`: indices of linear residuals
+- `jacobian_residual_available`: indicates whether the sparse Jacobian of the residuals is available
+- `hessian_residual_available`: indicates whether the sum of the sparse Hessians of the residuals is available
+- `Jv_residual_available`: indicates whether the Jacobian-vector product for the residuals is available
+- `Jtv_residual_available`: indicates whether the transpose Jacobian-vector product for the residuals is available
+- `Hv_residual_available`: indicates whether the sum of Hessian-vector product for the residuals is available
 
 `NLSMeta` also contains the following attributes, which are computed from the variables above:
 - `nequ`: size of the residual
@@ -35,6 +40,12 @@ struct NLSMeta{T, S}
   lin::Vector{Int} # List of linear residuals
   nlin::Int # = length(lin)
 
+  jacobian_residual_available::Bool
+  hessian_residual_available::Bool
+  Jv_residual_available::Bool
+  Jtv_residual_available::Bool
+  Hv_residual_available::Bool
+
   function NLSMeta{T, S}(
     nequ::Int,
     nvar::Int;
@@ -42,6 +53,11 @@ struct NLSMeta{T, S}
     nnzj = nequ * nvar,
     nnzh = div(nvar * (nvar + 1), 2),
     lin = Int[],
+    jacobian_residual_available::Bool = true,
+    hessian_residual_available::Bool = true,
+    Jv_residual_available::Bool = true,
+    Jtv_residual_available::Bool = true,
+    Hv_residual_available::Bool = true,
   ) where {T, S}
     nnzj = max(0, nnzj)
     nnzh = max(0, nnzh)
@@ -50,7 +66,9 @@ struct NLSMeta{T, S}
     nlin = length(lin)
     nnln = length(nln)
 
-    return new{T, S}(nequ, nvar, x0, nnzj, nnzh, nln, nnln, lin, nlin)
+    return new{T, S}(nequ, nvar, x0, nnzj, nnzh, nln, nnln, lin, nlin,
+                     jacobian_residual_available, hessian_residual_available, Jv_residual_available,
+                     Jtv_residual_available, Hv_residual_available)
   end
 end