diff --git a/docs/extras/modules/data_connection/vectorstores/integrations/xata.mdx b/docs/extras/modules/data_connection/vectorstores/integrations/xata.mdx
new file mode 100644
index 000000000000..a5888669533b
--- /dev/null
+++ b/docs/extras/modules/data_connection/vectorstores/integrations/xata.mdx
@@ -0,0 +1,52 @@
+# Xata
+
+[Xata](https://xata.io) is a serverless data platform, based on PostgreSQL. It provides a type-safe TypeScript/JavaScript SDK for interacting with your database, and a UI for managing your data.
+
+Xata has a native vector type, which can be added to any table, and supports similarity search. LangChain inserts vectors directly to Xata, and queries it for the nearest neighbors of a given vector, so that you can use all the LangChain Embeddings integrations with Xata.
+
+## Setup
+
+### Install the Xata CLI
+
+```bash
+npm install @xata.io/cli -g
+```
+
+### Create a database to be used as a vector store
+
+In the [Xata UI](https://app.xata.io) create a new database. You can name it whatever you want, but for this example we'll use `langchain`.
+Create a table, again you can name it anything, but we will use `vectors`. Add the following columns via the UI:
+
+* `content` of type "Long text". This is used to store the `Document.pageContent` values.
+* `embedding` of type "Vector". Use the dimension used by the model you plan to use (1536 for OpenAI).
+* any other columns you want to use as metadata. They are populated from the `Document.metadata` object. For example, if in the `Document.metadata` object you have a `title` property, you can create a `title` column in the table and it will be populated.
+
+### Initialize the project
+
+In your project, run:
+
+```bash
+xata init
+```
+
+and then choose the database you created above. This will also generate a `xata.ts` or `xata.js` file that defines the client you can use to interact with the database. See the [Xata getting started docs](https://xata.io/docs/getting-started/installation) for more details on using the Xata JavaScript/TypeScript SDK.
+
+## Usage
+
+import CodeBlock from "@theme/CodeBlock";
+
+### Example: Q&A chatbot using OpenAI and Xata as vector store
+
+This example uses the `VectorDBQAChain` to search the documents stored in Xata and then pass them as context to the OpenAI model, in order to answer the question asked by the user.
+
+import FromDocs from "@examples/indexes/vector_stores/xata.ts";
+
+<CodeBlock language="typescript">{FromDocs}</CodeBlock>
+
+### Example: Similarity search with a metadata filter
+
+This example shows how to implement semantic search using LangChain.js and Xata. Before running it, make sure to add an `author` column of type String to the `vectors` table in Xata.
+
+import SimSearch from "@examples/indexes/vector_stores/xata_metadata.ts";
+
+<CodeBlock language="typescript">{SimSearch}</CodeBlock>
diff --git a/examples/package.json b/examples/package.json
index d8981b88cd2d..a5bf5536f046 100644
--- a/examples/package.json
+++ b/examples/package.json
@@ -35,6 +35,7 @@
     "@tensorflow/tfjs-backend-cpu": "^4.4.0",
     "@tigrisdata/vector": "^1.1.0",
     "@upstash/redis": "^1.20.6",
+    "@xata.io/client": "^0.25.1",
     "@zilliz/milvus2-sdk-node": "^2.2.7",
     "axios": "^0.26.0",
     "chromadb": "^1.4.0",
diff --git a/examples/src/indexes/vector_stores/xata.ts b/examples/src/indexes/vector_stores/xata.ts
new file mode 100644
index 000000000000..7319e863c9c5
--- /dev/null
+++ b/examples/src/indexes/vector_stores/xata.ts
@@ -0,0 +1,65 @@
+import { XataVectorSearch } from "langchain/vectorstores/xata";
+import { OpenAIEmbeddings } from "langchain/embeddings/openai";
+import { BaseClient } from "@xata.io/client";
+import { Document } from "langchain/document";
+import { VectorDBQAChain } from "langchain/chains";
+import { OpenAI } from "langchain/llms/openai";
+
+// First, follow set-up instructions at
+// https://js.langchain.com/docs/modules/data_connection/vectorstores/integrations/xata
+
+// if you use the generated client, you don't need this function.
+// Just import getXataClient from the generated xata.ts instead.
+const getXataClient = () => {
+  if (!process.env.XATA_API_KEY) {
+    throw new Error("XATA_API_KEY not set");
+  }
+
+  if (!process.env.XATA_DB_URL) {
+    throw new Error("XATA_DB_URL not set");
+  }
+  const xata = new BaseClient({
+    databaseURL: process.env.XATA_DB_URL,
+    apiKey: process.env.XATA_API_KEY,
+    branch: process.env.XATA_BRANCH || "main",
+  });
+  return xata;
+};
+
+export async function run() {
+  const client = getXataClient();
+
+  const table = "vectors";
+  const embeddings = new OpenAIEmbeddings();
+  const store = new XataVectorSearch(embeddings, { client, table });
+
+  // Add documents
+  const docs = [
+    new Document({
+      pageContent: "Xata is a Serverless Data platform based on PostgreSQL",
+    }),
+    new Document({
+      pageContent:
+        "Xata offers a built-in vector type that can be used to store and query vectors",
+    }),
+    new Document({
+      pageContent: "Xata includes similarity search",
+    }),
+  ];
+
+  const ids = await store.addDocuments(docs);
+
+  // eslint-disable-next-line no-promise-executor-return
+  await new Promise((r) => setTimeout(r, 2000));
+
+  const model = new OpenAI();
+  const chain = VectorDBQAChain.fromLLM(model, store, {
+    k: 1,
+    returnSourceDocuments: true,
+  });
+  const response = await chain.call({ query: "What is Xata?" });
+
+  console.log(JSON.stringify(response, null, 2));
+
+  await store.delete({ ids });
+}
diff --git a/examples/src/indexes/vector_stores/xata_metadata.ts b/examples/src/indexes/vector_stores/xata_metadata.ts
new file mode 100644
index 000000000000..306534a894f0
--- /dev/null
+++ b/examples/src/indexes/vector_stores/xata_metadata.ts
@@ -0,0 +1,61 @@
+import { XataVectorSearch } from "langchain/vectorstores/xata";
+import { OpenAIEmbeddings } from "langchain/embeddings/openai";
+import { BaseClient } from "@xata.io/client";
+import { Document } from "langchain/document";
+
+// First, follow set-up instructions at
+// https://js.langchain.com/docs/modules/data_connection/vectorstores/integrations/xata
+// Also, add a column named "author" to the "vectors" table.
+
+// if you use the generated client, you don't need this function.
+// Just import getXataClient from the generated xata.ts instead.
+const getXataClient = () => {
+  if (!process.env.XATA_API_KEY) {
+    throw new Error("XATA_API_KEY not set");
+  }
+
+  if (!process.env.XATA_DB_URL) {
+    throw new Error("XATA_DB_URL not set");
+  }
+  const xata = new BaseClient({
+    databaseURL: process.env.XATA_DB_URL,
+    apiKey: process.env.XATA_API_KEY,
+    branch: process.env.XATA_BRANCH || "main",
+  });
+  return xata;
+};
+
+export async function run() {
+  const client = getXataClient();
+  const table = "vectors";
+  const embeddings = new OpenAIEmbeddings();
+  const store = new XataVectorSearch(embeddings, { client, table });
+  // Add documents
+  const docs = [
+    new Document({
+      pageContent: "Xata works great with Langchain.js",
+      metadata: { author: "Xata" },
+    }),
+    new Document({
+      pageContent: "Xata works great with Langchain",
+      metadata: { author: "Langchain" },
+    }),
+    new Document({
+      pageContent: "Xata includes similarity search",
+      metadata: { author: "Xata" },
+    }),
+  ];
+  const ids = await store.addDocuments(docs);
+
+  // eslint-disable-next-line no-promise-executor-return
+  await new Promise((r) => setTimeout(r, 2000));
+
+  // author is applied as pre-filter to the similarity search
+  const results = await store.similaritySearchWithScore("xata works great", 6, {
+    author: "Langchain",
+  });
+
+  console.log(JSON.stringify(results, null, 2));
+
+  await store.delete({ ids });
+}
diff --git a/langchain/.gitignore b/langchain/.gitignore
index 1a9c0d974deb..be60fae4e5f4 100644
--- a/langchain/.gitignore
+++ b/langchain/.gitignore
@@ -202,6 +202,9 @@ vectorstores/tigris.d.ts
 vectorstores/vectara.cjs
 vectorstores/vectara.js
 vectorstores/vectara.d.ts
+vectorstores/xata.cjs
+vectorstores/xata.js
+vectorstores/xata.d.ts
 text_splitter.cjs
 text_splitter.js
 text_splitter.d.ts
diff --git a/langchain/package.json b/langchain/package.json
index 20e681f93045..0d6741c65e34 100644
--- a/langchain/package.json
+++ b/langchain/package.json
@@ -214,6 +214,9 @@
     "vectorstores/vectara.cjs",
     "vectorstores/vectara.js",
     "vectorstores/vectara.d.ts",
+    "vectorstores/xata.cjs",
+    "vectorstores/xata.js",
+    "vectorstores/xata.d.ts",
     "text_splitter.cjs",
     "text_splitter.js",
     "text_splitter.d.ts",
@@ -574,6 +577,7 @@
     "@typescript-eslint/eslint-plugin": "^5.58.0",
     "@typescript-eslint/parser": "^5.58.0",
     "@upstash/redis": "^1.20.6",
+    "@xata.io/client": "^0.25.1",
     "@zilliz/milvus2-sdk-node": ">=2.2.7",
     "apify-client": "^2.7.1",
     "axios": "^0.26.0",
@@ -655,6 +659,7 @@
     "@tensorflow/tfjs-core": "*",
     "@tigrisdata/vector": "^1.1.0",
     "@upstash/redis": "^1.20.6",
+    "@xata.io/client": "^0.25.1",
     "@zilliz/milvus2-sdk-node": ">=2.2.7",
     "apify-client": "^2.7.1",
     "axios": "*",
@@ -772,6 +777,9 @@
     "@upstash/redis": {
       "optional": true
     },
+    "@xata.io/client": {
+      "optional": true
+    },
     "@zilliz/milvus2-sdk-node": {
       "optional": true
     },
@@ -1267,6 +1275,11 @@
       "import": "./vectorstores/vectara.js",
       "require": "./vectorstores/vectara.cjs"
     },
+    "./vectorstores/xata": {
+      "types": "./vectorstores/xata.d.ts",
+      "import": "./vectorstores/xata.js",
+      "require": "./vectorstores/xata.cjs"
+    },
     "./text_splitter": {
       "types": "./text_splitter.d.ts",
       "import": "./text_splitter.js",
diff --git a/langchain/scripts/create-entrypoints.js b/langchain/scripts/create-entrypoints.js
index bc880032a385..c0eed9b4a0e0 100644
--- a/langchain/scripts/create-entrypoints.js
+++ b/langchain/scripts/create-entrypoints.js
@@ -84,6 +84,7 @@ const entrypoints = {
   "vectorstores/singlestore": "vectorstores/singlestore",
   "vectorstores/tigris": "vectorstores/tigris",
   "vectorstores/vectara": "vectorstores/vectara",
+  "vectorstores/xata": "vectorstores/xata",
   // text_splitter
   text_splitter: "text_splitter",
   // memory
@@ -197,7 +198,8 @@ const entrypoints = {
   "experimental/babyagi": "experimental/babyagi/index",
   "experimental/generative_agents": "experimental/generative_agents/index",
   "experimental/plan_and_execute": "experimental/plan_and_execute/index",
-  "experimental/multimodal_embeddings/googlevertexai": "experimental/multimodal_embeddings/googlevertexai",
+  "experimental/multimodal_embeddings/googlevertexai":
+    "experimental/multimodal_embeddings/googlevertexai",
   // evaluation
   evaluation: "evaluation/index",
 };
diff --git a/langchain/src/load/import_map.ts b/langchain/src/load/import_map.ts
index 885ff58991b0..83e166efdb4f 100644
--- a/langchain/src/load/import_map.ts
+++ b/langchain/src/load/import_map.ts
@@ -19,6 +19,7 @@ export * as vectorstores__base from "../vectorstores/base.js";
 export * as vectorstores__memory from "../vectorstores/memory.js";
 export * as vectorstores__prisma from "../vectorstores/prisma.js";
 export * as vectorstores__vectara from "../vectorstores/vectara.js";
+export * as vectorstores__xata from "../vectorstores/xata.js";
 export * as text_splitter from "../text_splitter.js";
 export * as memory from "../memory/index.js";
 export * as document from "../document.js";
diff --git a/langchain/src/vectorstores/tests/xata.int.test.ts b/langchain/src/vectorstores/tests/xata.int.test.ts
new file mode 100644
index 000000000000..cab301657669
--- /dev/null
+++ b/langchain/src/vectorstores/tests/xata.int.test.ts
@@ -0,0 +1,161 @@
+/* eslint-disable no-process-env */
+// eslint-disable-next-line import/no-extraneous-dependencies
+import { BaseClient } from "@xata.io/client";
+
+import { XataVectorSearch } from "../xata.js";
+import { OpenAIEmbeddings } from "../../embeddings/openai.js";
+import { Document } from "../../document.js";
+
+test.skip("XataVectorSearch integration", async () => {
+  if (!process.env.XATA_API_KEY) {
+    throw new Error("XATA_API_KEY not set");
+  }
+
+  if (!process.env.XATA_DB_URL) {
+    throw new Error("XATA_DB_URL not set");
+  }
+  const xata = new BaseClient({
+    databaseURL: process.env.XATA_DB_URL,
+    apiKey: process.env.XATA_API_KEY,
+    branch: process.env.XATA_BRANCH || "main",
+  });
+
+  const table = "docs";
+  const embeddings = new OpenAIEmbeddings();
+
+  const store = new XataVectorSearch(embeddings, { client: xata, table });
+  expect(store).toBeDefined();
+
+  const createdAt = new Date().getTime();
+
+  const ids1 = await store.addDocuments([
+    { pageContent: "hello", metadata: { a: createdAt + 1 } },
+    { pageContent: "car", metadata: { a: createdAt } },
+    { pageContent: "adjective", metadata: { a: createdAt } },
+    { pageContent: "hi", metadata: { a: createdAt } },
+  ]);
+
+  let results1 = await store.similaritySearch("hello!", 1);
+
+  // search store is eventually consistent so we need to retry if nothing is
+  // returned
+  for (let i = 0; i < 5 && results1.length === 0; i += 1) {
+    results1 = await store.similaritySearch("hello!", 1);
+    // eslint-disable-next-line no-promise-executor-return
+    await new Promise((r) => setTimeout(r, 1000));
+  }
+
+  expect(results1).toHaveLength(1);
+  expect(results1).toEqual([
+    new Document({ metadata: { a: createdAt + 1 }, pageContent: "hello" }),
+  ]);
+
+  const results2 = await store.similaritySearchWithScore("testing!", 6, {
+    a: createdAt,
+  });
+  expect(results2).toHaveLength(3);
+
+  const ids2 = await store.addDocuments(
+    [
+      { pageContent: "hello upserted", metadata: { a: createdAt + 1 } },
+      { pageContent: "car upserted", metadata: { a: createdAt } },
+      { pageContent: "adjective upserted", metadata: { a: createdAt } },
+      { pageContent: "hi upserted", metadata: { a: createdAt } },
+    ],
+    { ids: ids1 }
+  );
+
+  expect(ids1).toEqual(ids2);
+
+  const results3 = await store.similaritySearchWithScore("testing!", 6, {
+    a: createdAt,
+  });
+
+  expect(results3).toHaveLength(3);
+
+  await store.delete({ ids: ids1.slice(2) });
+
+  let results4 = await store.similaritySearchWithScore("testing!", 3, {
+    a: createdAt,
+  });
+  for (let i = 0; i < 5 && results4.length > 1; i += 1) {
+    results4 = await store.similaritySearchWithScore("testing!", 3, {
+      a: createdAt,
+    });
+    // eslint-disable-next-line no-promise-executor-return
+    await new Promise((r) => setTimeout(r, 1000));
+  }
+
+  expect(results4).toHaveLength(1);
+
+  await store.delete({ ids: ids1 });
+  let results5 = await store.similaritySearch("hello!", 1);
+  for (let i = 0; i < 5 && results1.length > 0; i += 1) {
+    results5 = await store.similaritySearch("hello!", 1);
+    // eslint-disable-next-line no-promise-executor-return
+    await new Promise((r) => setTimeout(r, 1000));
+  }
+  expect(results5).toHaveLength(0);
+});
+
+test.skip("Search a XataVectorSearch using a metadata filter", async () => {
+  if (!process.env.XATA_API_KEY) {
+    throw new Error("XATA_API_KEY not set");
+  }
+
+  if (!process.env.XATA_DB_URL) {
+    throw new Error("XATA_DB_URL not set");
+  }
+  const xata = new BaseClient({
+    databaseURL: process.env.XATA_DB_URL,
+    apiKey: process.env.XATA_API_KEY,
+    branch: process.env.XATA_BRANCH || "main",
+  });
+
+  const table = "docs";
+  const embeddings = new OpenAIEmbeddings();
+
+  const store = new XataVectorSearch(embeddings, { client: xata, table });
+  expect(store).toBeDefined();
+
+  const createdAt = new Date().getTime();
+
+  const ids = await store.addDocuments([
+    { pageContent: "hello 0", metadata: { a: createdAt } },
+    { pageContent: "hello 1", metadata: { a: createdAt + 1 } },
+    { pageContent: "hello 2", metadata: { a: createdAt + 2 } },
+    { pageContent: "hello 3", metadata: { a: createdAt + 3 } },
+  ]);
+
+  // search store is eventually consistent so we need to retry if nothing is
+  // returned
+  let results1 = await store.similaritySearch("hello!", 1);
+  for (let i = 0; i < 5 && results1.length < 4; i += 1) {
+    results1 = await store.similaritySearch("hello", 6);
+    // eslint-disable-next-line no-promise-executor-return
+    await new Promise((r) => setTimeout(r, 1000));
+  }
+
+  expect(results1).toHaveLength(4);
+
+  const results = await store.similaritySearch("hello", 1, {
+    a: createdAt + 2,
+  });
+  expect(results).toHaveLength(1);
+
+  expect(results).toEqual([
+    new Document({
+      metadata: { a: createdAt + 2 },
+      pageContent: "hello 2",
+    }),
+  ]);
+
+  await store.delete({ ids });
+  let results5 = await store.similaritySearch("hello!", 1);
+  for (let i = 0; i < 5 && results1.length > 0; i += 1) {
+    results5 = await store.similaritySearch("hello", 1);
+    // eslint-disable-next-line no-promise-executor-return
+    await new Promise((r) => setTimeout(r, 1000));
+  }
+  expect(results5).toHaveLength(0);
+});
diff --git a/langchain/src/vectorstores/xata.ts b/langchain/src/vectorstores/xata.ts
new file mode 100644
index 000000000000..c0719f25fbb0
--- /dev/null
+++ b/langchain/src/vectorstores/xata.ts
@@ -0,0 +1,104 @@
+import { BaseClient } from "@xata.io/client";
+import { VectorStore } from "./base.js";
+import { Embeddings } from "../embeddings/base.js";
+import { Document } from "../document.js";
+
+export interface XataClientArgs<XataClient> {
+  readonly client: XataClient;
+  readonly table: string;
+}
+
+type XataFilter = object;
+
+export class XataVectorSearch<
+  XataClient extends BaseClient
+> extends VectorStore {
+  declare FilterType: XataFilter;
+
+  private readonly client: XataClient;
+
+  private readonly table: string;
+
+  _vectorstoreType(): string {
+    return "xata";
+  }
+
+  constructor(embeddings: Embeddings, args: XataClientArgs<XataClient>) {
+    super(embeddings, args);
+
+    this.client = args.client;
+    this.table = args.table;
+  }
+
+  async addDocuments(documents: Document[], options?: { ids?: string[] }) {
+    const texts = documents.map(({ pageContent }) => pageContent);
+    return this.addVectors(
+      await this.embeddings.embedDocuments(texts),
+      documents,
+      options
+    );
+  }
+
+  async addVectors(
+    vectors: number[][],
+    documents: Document[],
+    options?: { ids?: string[] }
+  ) {
+    const rows = vectors
+      .map((embedding, idx) => ({
+        content: documents[idx].pageContent,
+        embedding,
+        ...documents[idx].metadata,
+      }))
+      .map((row, idx) => {
+        if (options?.ids) {
+          return { id: options.ids[idx], ...row };
+        }
+        return row;
+      });
+
+    const res = await this.client.db[this.table].createOrReplace(rows);
+    // Since we have an untyped BaseClient, it doesn't know the
+    // actual return type of the overload.
+    const results = res as unknown as { id: string }[];
+    const returnedIds = results.map((row) => row.id);
+    return returnedIds;
+  }
+
+  async delete(params: { ids: string[] }): Promise<void> {
+    const { ids } = params;
+    await this.client.db[this.table].delete(ids);
+  }
+
+  async similaritySearchVectorWithScore(
+    query: number[],
+    k: number,
+    filter?: XataFilter | undefined
+  ): Promise<[Document, number][]> {
+    const records = await this.client.db[this.table].vectorSearch(
+      "embedding",
+      query,
+      {
+        size: k,
+        filter,
+      }
+    );
+
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    return records.map((record: any) => [
+      new Document({
+        pageContent: record.content,
+        metadata: Object.fromEntries(
+          Object.entries(record).filter(
+            ([key]) =>
+              key !== "content" &&
+              key !== "embedding" &&
+              key !== "xata" &&
+              key !== "id"
+          )
+        ),
+      }),
+      record.xata.score,
+    ]);
+  }
+}
diff --git a/langchain/tsconfig.json b/langchain/tsconfig.json
index 11f09c28eac5..63eddb521200 100644
--- a/langchain/tsconfig.json
+++ b/langchain/tsconfig.json
@@ -97,6 +97,7 @@
       "src/vectorstores/singlestore.ts",
       "src/vectorstores/tigris.ts",
       "src/vectorstores/vectara.ts",
+      "src/vectorstores/xata.ts",
       "src/text_splitter.ts",
       "src/memory/index.ts",
       "src/memory/zep.ts",
diff --git a/test-exports-cf/src/entrypoints.js b/test-exports-cf/src/entrypoints.js
index 7a28aa29f78d..a583ff422a4e 100644
--- a/test-exports-cf/src/entrypoints.js
+++ b/test-exports-cf/src/entrypoints.js
@@ -18,6 +18,7 @@ export * from "langchain/vectorstores/base";
 export * from "langchain/vectorstores/memory";
 export * from "langchain/vectorstores/prisma";
 export * from "langchain/vectorstores/vectara";
+export * from "langchain/vectorstores/xata";
 export * from "langchain/text_splitter";
 export * from "langchain/memory";
 export * from "langchain/document";
diff --git a/test-exports-cjs/src/entrypoints.js b/test-exports-cjs/src/entrypoints.js
index ded8b3398217..d4b316f47d94 100644
--- a/test-exports-cjs/src/entrypoints.js
+++ b/test-exports-cjs/src/entrypoints.js
@@ -18,6 +18,7 @@ const vectorstores_base = require("langchain/vectorstores/base");
 const vectorstores_memory = require("langchain/vectorstores/memory");
 const vectorstores_prisma = require("langchain/vectorstores/prisma");
 const vectorstores_vectara = require("langchain/vectorstores/vectara");
+const vectorstores_xata = require("langchain/vectorstores/xata");
 const text_splitter = require("langchain/text_splitter");
 const memory = require("langchain/memory");
 const document = require("langchain/document");
diff --git a/test-exports-esbuild/src/entrypoints.js b/test-exports-esbuild/src/entrypoints.js
index 92dc77f660e7..afb2fb7b79c6 100644
--- a/test-exports-esbuild/src/entrypoints.js
+++ b/test-exports-esbuild/src/entrypoints.js
@@ -18,6 +18,7 @@ import * as vectorstores_base from "langchain/vectorstores/base";
 import * as vectorstores_memory from "langchain/vectorstores/memory";
 import * as vectorstores_prisma from "langchain/vectorstores/prisma";
 import * as vectorstores_vectara from "langchain/vectorstores/vectara";
+import * as vectorstores_xata from "langchain/vectorstores/xata";
 import * as text_splitter from "langchain/text_splitter";
 import * as memory from "langchain/memory";
 import * as document from "langchain/document";
diff --git a/test-exports-esm/src/entrypoints.js b/test-exports-esm/src/entrypoints.js
index 92dc77f660e7..afb2fb7b79c6 100644
--- a/test-exports-esm/src/entrypoints.js
+++ b/test-exports-esm/src/entrypoints.js
@@ -18,6 +18,7 @@ import * as vectorstores_base from "langchain/vectorstores/base";
 import * as vectorstores_memory from "langchain/vectorstores/memory";
 import * as vectorstores_prisma from "langchain/vectorstores/prisma";
 import * as vectorstores_vectara from "langchain/vectorstores/vectara";
+import * as vectorstores_xata from "langchain/vectorstores/xata";
 import * as text_splitter from "langchain/text_splitter";
 import * as memory from "langchain/memory";
 import * as document from "langchain/document";
diff --git a/test-exports-vercel/src/entrypoints.js b/test-exports-vercel/src/entrypoints.js
index 7a28aa29f78d..a583ff422a4e 100644
--- a/test-exports-vercel/src/entrypoints.js
+++ b/test-exports-vercel/src/entrypoints.js
@@ -18,6 +18,7 @@ export * from "langchain/vectorstores/base";
 export * from "langchain/vectorstores/memory";
 export * from "langchain/vectorstores/prisma";
 export * from "langchain/vectorstores/vectara";
+export * from "langchain/vectorstores/xata";
 export * from "langchain/text_splitter";
 export * from "langchain/memory";
 export * from "langchain/document";
diff --git a/test-exports-vite/src/entrypoints.js b/test-exports-vite/src/entrypoints.js
index 7a28aa29f78d..a583ff422a4e 100644
--- a/test-exports-vite/src/entrypoints.js
+++ b/test-exports-vite/src/entrypoints.js
@@ -18,6 +18,7 @@ export * from "langchain/vectorstores/base";
 export * from "langchain/vectorstores/memory";
 export * from "langchain/vectorstores/prisma";
 export * from "langchain/vectorstores/vectara";
+export * from "langchain/vectorstores/xata";
 export * from "langchain/text_splitter";
 export * from "langchain/memory";
 export * from "langchain/document";
diff --git a/yarn.lock b/yarn.lock
index a72091b35c10..804243f7636c 100644
--- a/yarn.lock
+++ b/yarn.lock
@@ -6786,6 +6786,15 @@ __metadata:
   languageName: node
   linkType: hard
 
+"@xata.io/client@npm:^0.25.1":
+  version: 0.25.1
+  resolution: "@xata.io/client@npm:0.25.1"
+  peerDependencies:
+    typescript: ">=4.5"
+  checksum: 041988667b19e84a4af27b8abb6c3ca79904df595a687e4a8cd19ce0c1e3d180781fb2e54ba55de2217893f76b05048cffa99d171034f9a4229d694904d43bcd
+  languageName: node
+  linkType: hard
+
 "@zilliz/milvus2-sdk-node@npm:>=2.2.7, @zilliz/milvus2-sdk-node@npm:^2.2.7":
   version: 2.2.10
   resolution: "@zilliz/milvus2-sdk-node@npm:2.2.10"
@@ -10060,6 +10069,7 @@ __metadata:
     "@typescript-eslint/eslint-plugin": ^5.51.0
     "@typescript-eslint/parser": ^5.51.0
     "@upstash/redis": ^1.20.6
+    "@xata.io/client": ^0.25.1
     "@zilliz/milvus2-sdk-node": ^2.2.7
     axios: ^0.26.0
     chromadb: ^1.4.0
@@ -13137,6 +13147,7 @@ __metadata:
     "@typescript-eslint/eslint-plugin": ^5.58.0
     "@typescript-eslint/parser": ^5.58.0
     "@upstash/redis": ^1.20.6
+    "@xata.io/client": ^0.25.1
     "@zilliz/milvus2-sdk-node": ">=2.2.7"
     ansi-styles: ^5.0.0
     apify-client: ^2.7.1
@@ -13237,6 +13248,7 @@ __metadata:
     "@tensorflow/tfjs-core": "*"
     "@tigrisdata/vector": ^1.1.0
     "@upstash/redis": ^1.20.6
+    "@xata.io/client": ^0.25.1
     "@zilliz/milvus2-sdk-node": ">=2.2.7"
     apify-client: ^2.7.1
     axios: "*"
@@ -13326,6 +13338,8 @@ __metadata:
       optional: true
     "@upstash/redis":
       optional: true
+    "@xata.io/client":
+      optional: true
     "@zilliz/milvus2-sdk-node":
       optional: true
     apify-client: