@@ -166,7 +166,7 @@ describeWithMongoDB(
166166            const  response  =  await  integration . mcpClient ( ) . callTool ( { 
167167                name : "insert-many" , 
168168                arguments : { 
169-                     database : integration . randomDbName ( ) , 
169+                     database : database , 
170170                    collection : "test" , 
171171                    documents : [ {  embedding : "oopsie"  } ] , 
172172                } , 
@@ -237,7 +237,7 @@ describeWithMongoDB(
237237            } ) ; 
238238
239239            it ( "generates embeddings for multiple documents with the same field" ,  async  ( )  =>  { 
240-                 await  createVectorSearchIndexAndWait ( integration . mongoClient ( ) ,  integration . randomDbName ( ) ,  "test" ,  [ 
240+                 await  createVectorSearchIndexAndWait ( integration . mongoClient ( ) ,  database ,  "test" ,  [ 
241241                    { 
242242                        type : "vector" , 
243243                        path : "titleEmbeddings" , 
@@ -250,7 +250,7 @@ describeWithMongoDB(
250250                const  response  =  await  integration . mcpClient ( ) . callTool ( { 
251251                    name : "insert-many" , 
252252                    arguments : { 
253-                         database : integration . randomDbName ( ) , 
253+                         database : database , 
254254                        collection : "test" , 
255255                        documents : [ 
256256                            { 
@@ -388,7 +388,7 @@ describeWithMongoDB(
388388            } ) ; 
389389
390390            it ( "removes redundant nested field from document when embeddings are generated" ,  async  ( )  =>  { 
391-                 await  createVectorSearchIndexAndWait ( integration . mongoClient ( ) ,  integration . randomDbName ( ) ,  "test" ,  [ 
391+                 await  createVectorSearchIndexAndWait ( integration . mongoClient ( ) ,  database ,  "test" ,  [ 
392392                    { 
393393                        type : "vector" , 
394394                        path : "title.embeddings" , 
@@ -422,7 +422,7 @@ describeWithMongoDB(
422422            } ) ; 
423423
424424            it ( "returns an error when input field does not have a vector search index" ,  async  ( )  =>  { 
425-                 await  createVectorSearchIndexAndWait ( integration . mongoClient ( ) ,  integration . randomDbName ( ) ,  "test" ,  [ 
425+                 await  createVectorSearchIndexAndWait ( integration . mongoClient ( ) ,  database ,  "test" ,  [ 
426426                    { 
427427                        type : "vector" , 
428428                        path : "titleEmbeddings" , 
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