diff --git a/src-tauri/src/db.rs b/src-tauri/src/db.rs
index 8ca3fd3..be303ec 100644
--- a/src-tauri/src/db.rs
+++ b/src-tauri/src/db.rs
@@ -43,7 +43,7 @@
             END;
             CREATE VIRTUAL TABLE IF NOT EXISTS vec_items USING vec0(
                 id INTEGER PRIMARY KEY,
-                embedding FLOAT[3]
+                embedding FLOAT[384]
             );",
         )?;
     }
diff --git a/src/backend/config.js b/src/backend/config.js
index bd7b687..778afb1 100644
--- a/src/backend/config.js
+++ b/src/backend/config.js
@@ -28,7 +28,7 @@
   // ベクトルDB
   database: {
     filename: process.env.DB_PATH || "vector.db",
-    embeddingDim: Number(process.env.VEC_DIM ?? 3),
+    embeddingDim: Number(process.env.VEC_DIM ?? 384),
   },
 
   // ロギング
diff --git a/test/mcp-handlers.test.js b/test/mcp-handlers.test.js
index 99b129c..c861b14 100644
--- a/test/mcp-handlers.test.js
+++ b/test/mcp-handlers.test.js
@@ -16,13 +16,13 @@
 
   it("should validate embedding dimension correctly", () => {
     const testVectors = [
-      { dim: 3, valid: true },
+      { dim: 384, valid: true },
       { dim: 2, valid: false },
-      { dim: 4, valid: false },
+      { dim: 385, valid: false },
     ];
 
-    const EMBEDDING_DIM = Number(process.env.VEC_DIM ?? 3);
-    
+    const EMBEDDING_DIM = Number(process.env.VEC_DIM ?? 384);
+
     testVectors.forEach(({ dim, valid }) => {
       const vector = new Array(dim).fill(0.5);
       const isValid = vector.length === EMBEDDING_DIM;
diff --git a/test/setup.js b/test/setup.js
index d168b92..a723c8a 100644
--- a/test/setup.js
+++ b/test/setup.js
@@ -11,7 +11,7 @@
   } catch (err) {
     // ロックされているファイルは無視して続行
   }
-  
+
   const db = new Database(dbName);
   return db;
 }
@@ -30,7 +30,7 @@
 
 // テスト用環境変数の設定
 export function setTestEnv() {
-  process.env.VEC_DIM = "3";
+  process.env.VEC_DIM = "384";
   process.env.LLAMA_CPP_BASE_URL = "http://127.0.0.1:8080";
   process.env.LLAMA_CPP_EMBEDDING_MODEL = "nomic-embed-text";
   process.env.LLAMA_CPP_MODEL = "mistral";