chore: rename vectorSearch feature flag to search (#760)

Author: nirinchev

README.md

@@ -499,12 +499,12 @@ You can disable telemetry using:
 
 The MongoDB MCP Server may offer functionality that is still in development and may change in future releases. These features are considered "preview features" and are not enabled by default. Generally, these features are well tested, but may not offer the complete functionality we intend to provide in the final release or we'd like to gather feedback before making them generally available. To enable one or more preview features, use the `previewFeatures` configuration option.
 
-- For **environment variable** configuration, use a comma-separated string: `export MDB_MCP_PREVIEW_FEATURES="vectorSearch,feature1,feature2"`.
-- For **command-line argument** configuration, use a space-separated string: `--previewFeatures vectorSearch feature1 feature2`.
+- For **environment variable** configuration, use a comma-separated string: `export MDB_MCP_PREVIEW_FEATURES="search,feature1,feature2"`.
+- For **command-line argument** configuration, use a space-separated string: `--previewFeatures search feature1 feature2`.
 
 List of available preview features:
 
-- `vectorSearch` - Enables tools or functionality related to Vector Search in MongoDB Atlas:
+- `search` - Enables tools or functionality related to Atlas Search and Vector Search in MongoDB Atlas:
   - Index management, such as creating, listing, and dropping search and vector search indexes.
   - Querying collections using vector search capabilities. This requires a configured embedding model that will be used to generate vector representations of the query data. Currently, only [Voyage AI](https://www.voyageai.com) embedding models are supported. Set the `voyageApiKey` configuration option with your Voyage AI API key to use this feature.
 

package.json

@@ -70,6 +70,7 @@
     "test": "vitest --project eslint-rules --project unit-and-integration --coverage",
     "test:accuracy": "sh ./scripts/accuracy/runAccuracyTests.sh",
     "test:long-running-tests": "vitest --project long-running-tests --coverage",
+    "test:local": "SKIP_ATLAS_TESTS=true SKIP_ATLAS_LOCAL_TESTS=true pnpm run test",
     "atlas:cleanup": "vitest --project atlas-cleanup"
   },
   "license": "Apache-2.0",

src/common/config/createUserConfig.ts

@@ -170,19 +170,19 @@ function registerKnownSecretsInRootKeychain(userConfig: Partial<UserConfig>): vo
 }
 
 function warnIfVectorSearchNotEnabledCorrectly(config: UserConfig, warn: (message: string) => void): void {
-    const vectorSearchEnabled = config.previewFeatures.includes("vectorSearch");
+    const searchEnabled = config.previewFeatures.includes("search");
     const embeddingsProviderConfigured = !!config.voyageApiKey;
-    if (vectorSearchEnabled && !embeddingsProviderConfigured) {
+    if (searchEnabled && !embeddingsProviderConfigured) {
         warn(`\
 Warning: Vector search is enabled but no embeddings provider is configured.
 - Set an embeddings provider configuration option to enable auto-embeddings during document insertion and text-based queries with $vectorSearch.\
 `);
     }
 
-    if (!vectorSearchEnabled && embeddingsProviderConfigured) {
+    if (!searchEnabled && embeddingsProviderConfigured) {
         warn(`\
-Warning: An embeddings provider is configured but the 'vectorSearch' preview feature is not enabled.
-- Enable vector search by adding 'vectorSearch' to the 'previewFeatures' configuration option, or remove the embeddings provider configuration if not needed.\
+Warning: An embeddings provider is configured but the 'search' preview feature is not enabled.
+- Enable vector search by adding 'search' to the 'previewFeatures' configuration option, or remove the embeddings provider configuration if not needed.\
 `);
     }
 }

src/common/schemas.ts

@@ -1,4 +1,4 @@
-export const previewFeatureValues = ["vectorSearch"] as const;
+export const previewFeatureValues = ["search"] as const;
 export type PreviewFeature = (typeof previewFeatureValues)[number];
 
 export const similarityValues = ["cosine", "euclidean", "dotProduct"] as const;

src/common/search/embeddingsProvider.ts

@@ -41,7 +41,7 @@ class VoyageEmbeddingsProvider implements EmbeddingsProvider<VoyageModels, Voyag
     }
 
     static isConfiguredIn({ voyageApiKey, previewFeatures }: UserConfig): boolean {
-        return previewFeatures.includes("vectorSearch") && !!voyageApiKey;
+        return previewFeatures.includes("search") && !!voyageApiKey;
     }
 
     async embed<Model extends VoyageModels>(

src/tools/mongodb/create/createIndex.ts

@@ -76,11 +76,11 @@ export class CreateIndexTool extends MongoDBToolBase {
                         type: z.literal("classic"),
                         keys: z.object({}).catchall(z.custom<IndexDirection>()).describe("The index definition"),
                     }),
-                    ...(this.isFeatureEnabled("vectorSearch") ? [this.vectorSearchIndexDefinition] : []),
+                    ...(this.isFeatureEnabled("search") ? [this.vectorSearchIndexDefinition] : []),
                 ])
             )
             .describe(
-                `The index definition. Use 'classic' for standard indexes${this.isFeatureEnabled("vectorSearch") ? " and 'vectorSearch' for vector search indexes" : ""}.`
+                `The index definition. Use 'classic' for standard indexes${this.isFeatureEnabled("search") ? " and 'vectorSearch' for vector search indexes" : ""}.`
             ),
     };
 

src/tools/mongodb/create/insertMany.ts

@@ -25,7 +25,7 @@ export class InsertManyTool extends MongoDBToolBase {
             .describe(
                 "The array of documents to insert, matching the syntax of the document argument of db.collection.insertMany()."
             ),
-        ...(this.isFeatureEnabled("vectorSearch")
+        ...(this.isFeatureEnabled("search")
             ? {
                   embeddingParameters: zSupportedEmbeddingParametersWithInput
                       .optional()
@@ -45,7 +45,7 @@ export class InsertManyTool extends MongoDBToolBase {
     }: ToolArgs<typeof this.argsShape>): Promise<CallToolResult> {
         const provider = await this.ensureConnected();
 
-        const embeddingParameters = this.isFeatureEnabled("vectorSearch")
+        const embeddingParameters = this.isFeatureEnabled("search")
             ? (providedEmbeddingParameters as z.infer<typeof zSupportedEmbeddingParametersWithInput>)
             : undefined;
 

src/tools/mongodb/delete/dropIndex.ts

@@ -10,7 +10,7 @@ export class DropIndexTool extends MongoDBToolBase {
     protected argsShape = {
         ...DbOperationArgs,
         indexName: z.string().nonempty().describe("The name of the index to be dropped."),
-        type: this.isFeatureEnabled("vectorSearch")
+        type: this.isFeatureEnabled("search")
             ? z
                   .enum(["classic", "search"])
                   .describe(

src/tools/mongodb/metadata/collectionIndexes.ts

@@ -31,7 +31,7 @@ export class CollectionIndexesTool extends MongoDBToolBase {
         }));
 
         const searchIndexDefinitions: SearchIndexStatus[] = [];
-        if (this.isFeatureEnabled("vectorSearch") && (await this.session.isSearchSupported())) {
+        if (this.isFeatureEnabled("search") && (await this.session.isSearchSupported())) {
             const searchIndexes = await provider.getSearchIndexes(database, collection);
             searchIndexDefinitions.push(...this.extractSearchIndexDetails(searchIndexes));
         }

src/tools/mongodb/metadata/explain.ts

@@ -20,7 +20,7 @@ export class ExplainTool extends MongoDBToolBase {
                 z.discriminatedUnion("name", [
                     z.object({
                         name: z.literal("aggregate"),
-                        arguments: z.object(getAggregateArgs(this.isFeatureEnabled("vectorSearch"))),
+                        arguments: z.object(getAggregateArgs(this.isFeatureEnabled("search"))),
                     }),
                     z.object({
                         name: z.literal("find"),