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diff --git a/jstests/disk/repair_clustered_collection.js b/jstests/disk/repair_clustered_collection.js
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+++ b/jstests/disk/repair_clustered_collection.js
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+/**
+ * Tests that --repair on WiredTiger correctly and gracefully handles a missing _mdb_catalog when
+ * a clustered collection exists on the server instance.
+ *
+ * @tags: [requires_wiredtiger]
+ */
+(function() {
+
+load('jstests/disk/libs/wt_file_helper.js');
+load("jstests/libs/collection_drop_recreate.js");
+
+const dbName = jsTestName();
+const collName = "test";
+const dbpath = MongoRunner.dataPath + dbName + "/";
+
+const runRepairTest = function runRepairTestOnMongoDInstance(
+    collectionOptions, docToInsert, isTimeseries) {
+    let mongod = startMongodOnExistingPath(dbpath);
+    let db = mongod.getDB(dbName);
+
+    assertDropCollection(db, collName);
+    assertCreateCollection(db, collName, collectionOptions);
+
+    let testColl = db[collName];
+    let testCollUri = getUriForColl(testColl);
+    let testCollFile = dbpath + testCollUri + ".wt";
+
+    assert.commandWorked(testColl.insert(docToInsert));
+
+    // A document repaired from a timeseries collection will be in a different format than the
+    // original document. This is because the timeseries's system.views collection will be not be
+    // associated with the orphaned clustered collection. Thus, the data will show up as it would
+    // have in the raw system.buckets collection for the timeseries collection.
+    const expectedOrphanDoc =
+        isTimeseries ? db["system.buckets." + collName].findOne() : testColl.findOne();
+
+    MongoRunner.stopMongod(mongod);
+
+    // Delete the _mdb_catalog.
+    let mdbCatalogFile = dbpath + "_mdb_catalog.wt";
+    jsTestLog("deleting catalog file: " + mdbCatalogFile);
+    removeFile(mdbCatalogFile);
+
+    assertRepairSucceeds(dbpath, mongod.port);
+
+    // Verify that repair succeeds in creating an empty catalog and MongoDB starts up normally with
+    // no data.
+    mongod = startMongodOnExistingPath(dbpath);
+    db = mongod.getDB(dbName);
+    testColl = db[collName];
+    assert.isnull(testColl.exists());
+    assert.eq(testColl.find(docToInsert).itcount(), 0);
+    assert.eq(testColl.count(), 0);
+
+    // Ensure the orphaned collection is valid and the document is preserved.
+    const orphanedImportantCollName = "orphan." + testCollUri.replace(/-/g, "_");
+    const localDb = mongod.getDB("local");
+    orphanedCollection = localDb[orphanedImportantCollName];
+    assert(orphanedCollection.exists());
+    assert.eq(orphanedCollection.count(expectedOrphanDoc),
+              1,
+              `Expected to find document ${tojson(expectedOrphanDoc)} but collection has contents ${
+                  tojson(orphanedCollection.find().toArray())}`);
+
+    const validateResult = orphanedCollection.validate();
+    assert(validateResult.valid);
+    MongoRunner.stopMongod(mongod);
+};
+
+// Standard clustered collection test.
+let isTimeseries = false;
+let clusteredCollOptions = {clusteredIndex: {key: {_id: 1}, unique: true}};
+let docToInsert = {_id: 1};
+runRepairTest(clusteredCollOptions, docToInsert, isTimeseries);
+
+// Timeseries test since all timeseries collections are implicitly clustered.
+isTimeseries = true;
+clusteredCollOptions = {
+    timeseries: {timeField: "timestamp", metaField: "metadata", granularity: "hours"}
+};
+docToInsert = {
+    "metadata": {"sensorId": 5578, "type": "temperature"},
+    "timestamp": ISODate("2021-05-18T00:00:00.000Z"),
+    "temp": 12
+};
+runRepairTest(clusteredCollOptions, docToInsert, isTimeseries);
+})();