diff --git a/.github/workflows/pipeline.yml b/.github/workflows/pipeline.yml
index b8ba5fae..2a4f6695 100644
--- a/.github/workflows/pipeline.yml
+++ b/.github/workflows/pipeline.yml
@@ -1,6 +1,9 @@
 name: pipeline
 on: pull_request
 
+env:
+  REQUIRED_PHP_EXTENSIONS: 'mongodb'
+
 jobs:
   tests:
     runs-on: ubuntu-latest
@@ -16,6 +19,8 @@ jobs:
         uses: shivammathur/setup-php@v2
         with:
           php-version: ${{ matrix.php }}
+          coverage: "none"
+          extensions: "${{ env.REQUIRED_PHP_EXTENSIONS }}"
 
       - name: Install Composer
         uses: "ramsey/composer-install@v3"
@@ -41,6 +46,8 @@ jobs:
         uses: shivammathur/setup-php@v2
         with:
           php-version: '8.2'
+          coverage: "none"
+          extensions: "${{ env.REQUIRED_PHP_EXTENSIONS }}"
 
       - name: Install Composer
         uses: "ramsey/composer-install@v3"
diff --git a/README.md b/README.md
index bf1aef63..8ad25701 100644
--- a/README.md
+++ b/README.md
@@ -45,6 +45,7 @@ Supported Stores
 
 * [x] [ChromaDB](https://trychroma.com)
 * [x] [Azure AI Search](https://azure.microsoft.com/en-us/products/ai-services/ai-search)
+* [x] [MongoDB Atlas Search](https://mongodb.com/products/platform/atlas-vector-search)
 * [ ] [Pinecone](https://pinecone.io)
 
 Provided Tools
diff --git a/composer.json b/composer.json
index 545a2fa8..fdb83328 100644
--- a/composer.json
+++ b/composer.json
@@ -24,6 +24,7 @@
     },
     "require-dev": {
         "codewithkyrian/chromadb-php": "^0.2.1",
+        "mongodb/mongodb": "^1.19",
         "php-cs-fixer/shim": "^3.64",
         "phpstan/phpstan": "^1.12",
         "phpunit/phpunit": "^11.3",
@@ -36,6 +37,7 @@
         "symfony/var-dumper": "^6.4 || ^7.1"
     },
     "suggest": {
+        "mongodb/mongodb": "For using MongoDB Atlas as retrieval vector store.",
         "codewithkyrian/chromadb-php": "For using the ChromaDB as retrieval vector store.",
         "symfony/clock": "For using the clock tool.",
         "symfony/css-selector": "For using the YouTube transcription tool.",
diff --git a/src/Store/MongoDB/Store.php b/src/Store/MongoDB/Store.php
new file mode 100644
index 00000000..16836768
--- /dev/null
+++ b/src/Store/MongoDB/Store.php
@@ -0,0 +1,152 @@
+<?php
+
+declare(strict_types=1);
+
+namespace PhpLlm\LlmChain\Store\MongoDB;
+
+use MongoDB\BSON\Binary;
+use MongoDB\Client;
+use MongoDB\Collection;
+use PhpLlm\LlmChain\Document\Document;
+use PhpLlm\LlmChain\Document\Metadata;
+use PhpLlm\LlmChain\Document\Vector;
+use PhpLlm\LlmChain\Store\VectorStoreInterface;
+use Psr\Log\LoggerInterface;
+use Symfony\Component\Uid\Uuid;
+
+/**
+ * @see https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/
+ *
+ * For this store you need to create a separate MongoDB Atlas Search index.
+ * The index needs to be created with the following settings:
+ * {
+ *     "fields": [
+ *         {
+ *             "numDimensions": 1536,
+ *             "path": "vector",
+ *             "similarity": "euclidean",
+ *             "type": "vector"
+ *         }
+ *     ]
+ * }
+ *
+ * Note, that the `path` key needs to match the $vectorFieldName.
+ *
+ * For the `similarity` key you can choose between `euclidean`, `cosine` and `dotProduct`.
+ * {@see https://www.mongodb.com/docs/atlas/atlas-search/field-types/knn-vector/#define-the-index-for-the-fts-field-type-type}
+ *
+ * @author Oskar Stark <oskarstark@googlemail.com>
+ */
+final readonly class Store implements VectorStoreInterface
+{
+    /**
+     * @param string $databaseName    The name of the database
+     * @param string $collectionName  The name of the collection
+     * @param string $indexName       The name of the Atlas Search index
+     * @param string $vectorFieldName The name of the field int the index that contains the vector
+     * @param bool   $bulkWrite       Use bulk write operations
+     */
+    public function __construct(
+        private Client $client,
+        private LoggerInterface $logger,
+        private string $databaseName,
+        private string $collectionName,
+        private string $indexName,
+        private string $vectorFieldName = 'vector',
+        private bool $bulkWrite = false,
+    ) {
+    }
+
+    public function addDocument(Document $document): void
+    {
+        $this->addDocuments([$document]);
+    }
+
+    public function addDocuments(array $documents): void
+    {
+        $operations = [];
+
+        foreach ($documents as $document) {
+            if (!$document->hasVector()) {
+                $this->logger->warning('Document {id} does not have a vector', ['id' => $document->id]);
+            }
+
+            $operation = [
+                ['_id' => $this->toBinary($document->id)], // we use binary for the id, because of storage efficiency
+                array_filter([
+                    'metadata' => $document->metadata,
+                    $this->vectorFieldName => $document->vector->getData(),
+                    'text' => $document->text,
+                ]),
+                ['upsert' => true], // insert if not exists
+            ];
+
+            if ($this->bulkWrite) {
+                $operations[] = ['replaceOne' => $operation];
+                continue;
+            }
+
+            $this->getCollection()->replaceOne(...$operation);
+        }
+
+        if ($this->bulkWrite) {
+            $this->getCollection()->bulkWrite($operations);
+        }
+    }
+
+    /**
+     * @param array{
+     *     limit?: positive-int,
+     *     numCandidates?: positive-int,
+     *     filter?: array<mixed>
+     * } $options
+     *
+     * @return Document[]
+     */
+    public function query(Vector $vector, array $options = []): array
+    {
+        $results = $this->getCollection()->aggregate([
+            [
+                '$vectorSearch' => array_merge([
+                    'index' => $this->indexName,
+                    'path' => $this->vectorFieldName,
+                    'queryVector' => $vector->getData(),
+                    'numCandidates' => 200,
+                    'limit' => 5,
+                ], $options),
+            ],
+            [
+                '$addFields' => [
+                    'score' => ['$meta' => 'vectorSearchScore'],
+                ],
+            ],
+        ], ['typeMap' => ['root' => 'array', 'document' => 'array', 'array' => 'array']]);
+
+        $documents = [];
+
+        foreach ($results as $result) {
+            $documents[] = Document::fromVector(
+                Vector::create1536($result[$this->vectorFieldName]),
+                $this->toUuid($result['_id']),
+                new Metadata($result['metadata'] ?? []),
+            );
+        }
+
+        return $documents;
+    }
+
+    private function getCollection(): Collection
+    {
+        return $this->client->selectCollection($this->databaseName, $this->collectionName);
+    }
+
+    private function toBinary(Uuid $uuid): Binary
+    {
+        return new Binary($uuid->toBinary(), Binary::TYPE_UUID);
+    }
+
+    private function toUuid(Binary $binary): Uuid
+    {
+        return Uuid::fromString($binary->getData());
+    }
+}