diff --git a/ortools/linear_solver/samples/assignment_mip.cc b/ortools/linear_solver/samples/assignment_mip.cc
index 0fb00e1908..6b3d70b10e 100644
--- a/ortools/linear_solver/samples/assignment_mip.cc
+++ b/ortools/linear_solver/samples/assignment_mip.cc
@@ -34,7 +34,11 @@ void AssignmentMip() {
   // Solver
   // [START solver]
   // Create the mip solver with the SCIP backend.
-  MPSolver solver("assignment_mip", MPSolver::SCIP_MIXED_INTEGER_PROGRAMMING);
+  std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("SCIP"));
+  if (!solver) {
+    LOG(WARNING) << "SCIP solver unavailable.";
+    return;
+  }
   // [END solver]
 
   // Variables
@@ -45,7 +49,7 @@ void AssignmentMip() {
       num_workers, std::vector<const MPVariable*>(num_tasks));
   for (int i = 0; i < num_workers; ++i) {
     for (int j = 0; j < num_tasks; ++j) {
-      x[i][j] = solver.MakeIntVar(0, 1, "");
+      x[i][j] = solver->MakeIntVar(0, 1, "");
     }
   }
   // [END variables]
@@ -58,7 +62,7 @@ void AssignmentMip() {
     for (int j = 0; j < num_tasks; ++j) {
       worker_sum += x[i][j];
     }
-    solver.MakeRowConstraint(worker_sum <= 1.0);
+    solver->MakeRowConstraint(worker_sum <= 1.0);
   }
   // Each task is assigned to exactly one worker.
   for (int j = 0; j < num_tasks; ++j) {
@@ -66,13 +70,13 @@ void AssignmentMip() {
     for (int i = 0; i < num_workers; ++i) {
       task_sum += x[i][j];
     }
-    solver.MakeRowConstraint(task_sum == 1.0);
+    solver->MakeRowConstraint(task_sum == 1.0);
   }
   // [END constraints]
 
   // Objective.
   // [START objective]
-  MPObjective* const objective = solver.MutableObjective();
+  MPObjective* const objective = solver->MutableObjective();
   for (int i = 0; i < num_workers; ++i) {
     for (int j = 0; j < num_tasks; ++j) {
       objective->SetCoefficient(x[i][j], costs[i][j]);
@@ -83,7 +87,7 @@ void AssignmentMip() {
 
   // Solve
   // [START solve]
-  const MPSolver::ResultStatus result_status = solver.Solve();
+  const MPSolver::ResultStatus result_status = solver->Solve();
   // [END solve]
 
   // Print solution.
diff --git a/ortools/linear_solver/samples/bin_packing_mip.cc b/ortools/linear_solver/samples/bin_packing_mip.cc
index 05978788e9..078f46b837 100644
--- a/ortools/linear_solver/samples/bin_packing_mip.cc
+++ b/ortools/linear_solver/samples/bin_packing_mip.cc
@@ -41,7 +41,11 @@ void BinPackingMip() {
 
   // [START solver]
   // Create the mip solver with the SCIP backend.
-  MPSolver solver("bin_packing_mip", MPSolver::SCIP_MIXED_INTEGER_PROGRAMMING);
+  std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("SCIP"));
+  if (!solver) {
+    LOG(WARNING) << "SCIP solver unavailable.";
+    return;
+  }
   // [END solver]
 
   // [START program_part2]
@@ -50,13 +54,13 @@ void BinPackingMip() {
       data.num_items, std::vector<const MPVariable*>(data.num_bins));
   for (int i = 0; i < data.num_items; ++i) {
     for (int j = 0; j < data.num_bins; ++j) {
-      x[i][j] = solver.MakeIntVar(0.0, 1.0, "");
+      x[i][j] = solver->MakeIntVar(0.0, 1.0, "");
     }
   }
   // y[j] = 1 if bin j is used.
   std::vector<const MPVariable*> y(data.num_bins);
   for (int j = 0; j < data.num_bins; ++j) {
-    y[j] = solver.MakeIntVar(0.0, 1.0, "");
+    y[j] = solver->MakeIntVar(0.0, 1.0, "");
   }
   // [END variables]
 
@@ -68,7 +72,7 @@ void BinPackingMip() {
     for (int j = 0; j < data.num_bins; ++j) {
       sum += x[i][j];
     }
-    solver.MakeRowConstraint(sum == 1.0);
+    solver->MakeRowConstraint(sum == 1.0);
   }
   // For each bin that is used, the total packed weight can be at most
   // the bin capacity.
@@ -77,13 +81,13 @@ void BinPackingMip() {
     for (int i = 0; i < data.num_items; ++i) {
       weight += data.weights[i] * LinearExpr(x[i][j]);
     }
-    solver.MakeRowConstraint(weight <= LinearExpr(y[j]) * data.bin_capacity);
+    solver->MakeRowConstraint(weight <= LinearExpr(y[j]) * data.bin_capacity);
   }
   // [END constraints]
 
   // [START objective]
   // Create the objective function.
-  MPObjective* const objective = solver.MutableObjective();
+  MPObjective* const objective = solver->MutableObjective();
   LinearExpr num_bins_used;
   for (int j = 0; j < data.num_bins; ++j) {
     num_bins_used += y[j];
@@ -92,7 +96,7 @@ void BinPackingMip() {
   // [END objective]
 
   // [START solve]
-  const MPSolver::ResultStatus result_status = solver.Solve();
+  const MPSolver::ResultStatus result_status = solver->Solve();
   // [END solve]
 
   // [START print_solution]
diff --git a/ortools/linear_solver/samples/integer_programming_example.cc b/ortools/linear_solver/samples/integer_programming_example.cc
index 721a908707..2510efc27f 100644
--- a/ortools/linear_solver/samples/integer_programming_example.cc
+++ b/ortools/linear_solver/samples/integer_programming_example.cc
@@ -22,45 +22,48 @@ namespace operations_research {
 void IntegerProgrammingExample() {
   // [START solver]
   // Create the mip solver with the SCIP backend.
-  MPSolver solver("integer_programming_example",
-                  MPSolver::SCIP_MIXED_INTEGER_PROGRAMMING);
+  std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("SCIP"));
+  if (!solver) {
+    LOG(WARNING) << "SCIP solver unavailable.";
+    return;
+  }
   // [END solver]
 
   // [START variables]
   // x, y, and z are non-negative integer variables.
-  MPVariable* const x = solver.MakeIntVar(0.0, solver.infinity(), "x");
-  MPVariable* const y = solver.MakeIntVar(0.0, solver.infinity(), "y");
-  MPVariable* const z = solver.MakeIntVar(0.0, solver.infinity(), "z");
-  LOG(INFO) << "Number of variables = " << solver.NumVariables();
+  MPVariable* const x = solver->MakeIntVar(0.0, solver->infinity(), "x");
+  MPVariable* const y = solver->MakeIntVar(0.0, solver->infinity(), "y");
+  MPVariable* const z = solver->MakeIntVar(0.0, solver->infinity(), "z");
+  LOG(INFO) << "Number of variables = " << solver->NumVariables();
   // [END variables]
 
   // [START constraints]
   // 2*x + 7*y + 3*z <= 50
   MPConstraint* const constraint0 =
-      solver.MakeRowConstraint(-solver.infinity(), 50);
+      solver->MakeRowConstraint(-solver->infinity(), 50);
   constraint0->SetCoefficient(x, 2);
   constraint0->SetCoefficient(y, 7);
   constraint0->SetCoefficient(z, 3);
 
   // 3*x - 5*y + 7*z <= 45
   MPConstraint* const constraint1 =
-      solver.MakeRowConstraint(-solver.infinity(), 45);
+      solver->MakeRowConstraint(-solver->infinity(), 45);
   constraint1->SetCoefficient(x, 3);
   constraint1->SetCoefficient(y, -5);
   constraint1->SetCoefficient(z, 7);
 
   // 5*x + 2*y - 6*z <= 37
   MPConstraint* const constraint2 =
-      solver.MakeRowConstraint(-solver.infinity(), 37);
+      solver->MakeRowConstraint(-solver->infinity(), 37);
   constraint2->SetCoefficient(x, 5);
   constraint2->SetCoefficient(y, 2);
   constraint2->SetCoefficient(z, -6);
-  LOG(INFO) << "Number of constraints = " << solver.NumConstraints();
+  LOG(INFO) << "Number of constraints = " << solver->NumConstraints();
   // [END constraints]
 
   // [START objective]
   // Maximize 2*x + 2*y + 3*z
-  MPObjective* const objective = solver.MutableObjective();
+  MPObjective* const objective = solver->MutableObjective();
   objective->SetCoefficient(x, 2);
   objective->SetCoefficient(y, 2);
   objective->SetCoefficient(z, 3);
@@ -68,7 +71,7 @@ void IntegerProgrammingExample() {
   // [END objective]
 
   // [START solve]
-  const MPSolver::ResultStatus result_status = solver.Solve();
+  const MPSolver::ResultStatus result_status = solver->Solve();
   // Check that the problem has an optimal solution.
   if (result_status != MPSolver::OPTIMAL) {
     LOG(FATAL) << "The problem does not have an optimal solution!";
diff --git a/ortools/linear_solver/samples/linear_programming_example.cc b/ortools/linear_solver/samples/linear_programming_example.cc
index 91fce13002..a09dd9cabe 100644
--- a/ortools/linear_solver/samples/linear_programming_example.cc
+++ b/ortools/linear_solver/samples/linear_programming_example.cc
@@ -21,46 +21,49 @@
 namespace operations_research {
 void LinearProgrammingExample() {
   // [START solver]
-  MPSolver solver("linear_programming_examples",
-                  MPSolver::GLOP_LINEAR_PROGRAMMING);
+  std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("SCIP"));
+  if (!solver) {
+    LOG(WARNING) << "SCIP solver unavailable.";
+    return;
+  }
   // [END solver]
 
   // [START variables]
-  const double infinity = solver.infinity();
+  const double infinity = solver->infinity();
   // x and y are non-negative variables.
-  MPVariable* const x = solver.MakeNumVar(0.0, infinity, "x");
-  MPVariable* const y = solver.MakeNumVar(0.0, infinity, "y");
-  LOG(INFO) << "Number of variables = " << solver.NumVariables();
+  MPVariable* const x = solver->MakeNumVar(0.0, infinity, "x");
+  MPVariable* const y = solver->MakeNumVar(0.0, infinity, "y");
+  LOG(INFO) << "Number of variables = " << solver->NumVariables();
   // [END variables]
 
   // [START constraints]
   // x + 2*y <= 14.
-  MPConstraint* const c0 = solver.MakeRowConstraint(-infinity, 14.0);
+  MPConstraint* const c0 = solver->MakeRowConstraint(-infinity, 14.0);
   c0->SetCoefficient(x, 1);
   c0->SetCoefficient(y, 2);
 
   // 3*x - y >= 0.
-  MPConstraint* const c1 = solver.MakeRowConstraint(0.0, infinity);
+  MPConstraint* const c1 = solver->MakeRowConstraint(0.0, infinity);
   c1->SetCoefficient(x, 3);
   c1->SetCoefficient(y, -1);
 
   // x - y <= 2.
-  MPConstraint* const c2 = solver.MakeRowConstraint(-infinity, 2.0);
+  MPConstraint* const c2 = solver->MakeRowConstraint(-infinity, 2.0);
   c2->SetCoefficient(x, 1);
   c2->SetCoefficient(y, -1);
-  LOG(INFO) << "Number of constraints = " << solver.NumConstraints();
+  LOG(INFO) << "Number of constraints = " << solver->NumConstraints();
   // [END constraints]
 
   // [START objective]
   // Objective function: 3x + 4y.
-  MPObjective* const objective = solver.MutableObjective();
+  MPObjective* const objective = solver->MutableObjective();
   objective->SetCoefficient(x, 3);
   objective->SetCoefficient(y, 4);
   objective->SetMaximization();
   // [END objective]
 
   // [START solve]
-  const MPSolver::ResultStatus result_status = solver.Solve();
+  const MPSolver::ResultStatus result_status = solver->Solve();
   // Check that the problem has an optimal solution.
   if (result_status != MPSolver::OPTIMAL) {
     LOG(FATAL) << "The problem does not have an optimal solution!";
diff --git a/ortools/linear_solver/samples/mip_var_array.cc b/ortools/linear_solver/samples/mip_var_array.cc
index d60a63efef..d9aa62c9f8 100644
--- a/ortools/linear_solver/samples/mip_var_array.cc
+++ b/ortools/linear_solver/samples/mip_var_array.cc
@@ -41,34 +41,38 @@ void MipVarArray() {
 
   // [START solver]
   // Create the mip solver with the SCIP backend.
-  MPSolver solver("mip_var_array", MPSolver::SCIP_MIXED_INTEGER_PROGRAMMING);
+  std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("SCIP"));
+  if (!solver) {
+    LOG(WARNING) << "SCIP solver unavailable.";
+    return;
+  }
   // [END solver]
 
   // [START program_part2]
   // [START variables]
-  const double infinity = solver.infinity();
+  const double infinity = solver->infinity();
   // x[j] is an array of non-negative, integer variables.
   std::vector<const MPVariable*> x(data.num_vars);
   for (int j = 0; j < data.num_vars; ++j) {
-    x[j] = solver.MakeIntVar(0.0, infinity, "");
+    x[j] = solver->MakeIntVar(0.0, infinity, "");
   }
-  LOG(INFO) << "Number of variables = " << solver.NumVariables();
+  LOG(INFO) << "Number of variables = " << solver->NumVariables();
   // [END variables]
 
   // [START constraints]
   // Create the constraints.
   for (int i = 0; i < data.num_constraints; ++i) {
-    MPConstraint* constraint = solver.MakeRowConstraint(0, data.bounds[i], "");
+    MPConstraint* constraint = solver->MakeRowConstraint(0, data.bounds[i], "");
     for (int j = 0; j < data.num_vars; ++j) {
       constraint->SetCoefficient(x[j], data.constraint_coeffs[i][j]);
     }
   }
-  LOG(INFO) << "Number of constraints = " << solver.NumConstraints();
+  LOG(INFO) << "Number of constraints = " << solver->NumConstraints();
   // [END constraints]
 
   // [START objective]
   // Create the objective function.
-  MPObjective* const objective = solver.MutableObjective();
+  MPObjective* const objective = solver->MutableObjective();
   for (int j = 0; j < data.num_vars; ++j) {
     objective->SetCoefficient(x[j], data.obj_coeffs[j]);
   }
@@ -76,7 +80,7 @@ void MipVarArray() {
   // [END objective]
 
   // [START solve]
-  const MPSolver::ResultStatus result_status = solver.Solve();
+  const MPSolver::ResultStatus result_status = solver->Solve();
   // [END solve]
 
   // [START print_solution]
diff --git a/ortools/linear_solver/samples/multiple_knapsack_mip.cc b/ortools/linear_solver/samples/multiple_knapsack_mip.cc
index 15a836453b..6dfac219ae 100644
--- a/ortools/linear_solver/samples/multiple_knapsack_mip.cc
+++ b/ortools/linear_solver/samples/multiple_knapsack_mip.cc
@@ -44,8 +44,11 @@ void MultipleKnapsackMip() {
 
   // [START solver]
   // Create the mip solver with the SCIP backend.
-  MPSolver solver("multiple_knapsack_mip",
-                  MPSolver::SCIP_MIXED_INTEGER_PROGRAMMING);
+  std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("SCIP"));
+  if (!solver) {
+    LOG(WARNING) << "SCIP solver unavailable.";
+    return;
+  }
   // [END solver]
 
   // [START program_part2]
@@ -54,7 +57,7 @@ void MultipleKnapsackMip() {
       data.num_items, std::vector<const MPVariable*>(data.num_bins));
   for (int i = 0; i < data.num_items; ++i) {
     for (int j = 0; j < data.num_bins; ++j) {
-      x[i][j] = solver.MakeIntVar(0.0, 1.0, "");
+      x[i][j] = solver->MakeIntVar(0.0, 1.0, "");
     }
   }
   // [END variables]
@@ -67,7 +70,7 @@ void MultipleKnapsackMip() {
     for (int j = 0; j < data.num_bins; ++j) {
       sum += x[i][j];
     }
-    solver.MakeRowConstraint(sum <= 1.0);
+    solver->MakeRowConstraint(sum <= 1.0);
   }
   // For each bin that is used, the total packed weight can be at most
   // the bin capacity.
@@ -76,13 +79,13 @@ void MultipleKnapsackMip() {
     for (int i = 0; i < data.num_items; ++i) {
       weight += data.weights[i] * LinearExpr(x[i][j]);
     }
-    solver.MakeRowConstraint(weight <= data.bin_capacities[j]);
+    solver->MakeRowConstraint(weight <= data.bin_capacities[j]);
   }
   // [END constraints]
 
   // [START objective]
   // Create the objective function.
-  MPObjective* const objective = solver.MutableObjective();
+  MPObjective* const objective = solver->MutableObjective();
   LinearExpr value;
   for (int i = 0; i < data.num_items; ++i) {
     for (int j = 0; j < data.num_bins; ++j) {
@@ -93,7 +96,7 @@ void MultipleKnapsackMip() {
   // [END objective]
 
   // [START solve]
-  const MPSolver::ResultStatus result_status = solver.Solve();
+  const MPSolver::ResultStatus result_status = solver->Solve();
   // [END solve]
 
   // [START print_solution]
diff --git a/ortools/linear_solver/samples/simple_mip_program.cc b/ortools/linear_solver/samples/simple_mip_program.cc
index 4bc7d3eb81..f50e1fbaf4 100644
--- a/ortools/linear_solver/samples/simple_mip_program.cc
+++ b/ortools/linear_solver/samples/simple_mip_program.cc
@@ -22,6 +22,10 @@ void SimpleMipProgram() {
   // [START solver]
   // Create the mip solver with the SCIP backend.
   std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("SCIP"));
+  if (!solver) {
+    LOG(WARNING) << "SCIP solver unavailable.";
+    return;
+  }
   // [END solver]
 
   // [START variables]