diff --git a/API명세서.md b/API명세서.md
index bc94468..10f3c8c 100644
--- a/API명세서.md
+++ b/API명세서.md
@@ -559,10 +559,10 @@ MCP 서버를 초기화하고 서버 정보 및 지원 기능을 반환합니다
   "result": {
     "contents": [
       {
-        "uri": "memory://recent",
-        "mimeType": "application/json",
+    "uri": "memory://recent",
+    "mimeType": "application/json",
         "text": "{\"message\": \"Resource content for memory://recent\"}"
-      }
+    }
     ]
   }
 }
diff --git a/src/main/java/com/pandol365/dewey/api/controller/McpController.java b/src/main/java/com/pandol365/dewey/api/controller/McpController.java
index f3743d2..e9e9132 100644
--- a/src/main/java/com/pandol365/dewey/api/controller/McpController.java
+++ b/src/main/java/com/pandol365/dewey/api/controller/McpController.java
@@ -180,7 +180,7 @@ public class McpController {
                     toolArguments = params.getArguments();
                 }
 
-                yield mcpService.callTool(toolName, toolArguments);
+                    yield mcpService.callTool(toolName, toolArguments);
             }
             case "resources/list" -> mcpService.listResources();
             case "resources/read" -> {
diff --git a/src/main/java/com/pandol365/dewey/config/DatabaseInitializer.java b/src/main/java/com/pandol365/dewey/config/DatabaseInitializer.java
new file mode 100644
index 0000000..c85728b
--- /dev/null
+++ b/src/main/java/com/pandol365/dewey/config/DatabaseInitializer.java
@@ -0,0 +1,104 @@
+package com.pandol365.dewey.config;
+
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.boot.CommandLineRunner;
+import org.springframework.core.annotation.Order;
+import org.springframework.jdbc.core.JdbcTemplate;
+import org.springframework.stereotype.Component;
+
+/**
+ * 데이터베이스 초기화
+ * 프로젝트 시작 시 pgvector 확장 및 테이블 자동 생성
+ */
+@Slf4j
+@Component
+@Order(1) // 다른 초기화보다 먼저 실행
+@RequiredArgsConstructor
+public class DatabaseInitializer implements CommandLineRunner {
+
+    private final JdbcTemplate jdbcTemplate;
+
+    @Override
+    public void run(String... args) {
+        try {
+            log.info("=== 데이터베이스 초기화 시작 ===");
+            
+            // 1. pgvector 확장 확인 및 생성
+            initializePgVectorExtension();
+            
+            // 2. memory_embeddings 테이블 생성
+            createMemoryEmbeddingsTable();
+            
+            // 3. 인덱스 생성
+            createVectorIndex();
+            
+            log.info("=== 데이터베이스 초기화 완료 ===");
+            
+        } catch (Exception e) {
+            log.error("데이터베이스 초기화 실패: {}", e.getMessage(), e);
+            // 초기화 실패해도 애플리케이션은 계속 실행 (이미 존재하는 경우 등)
+        }
+    }
+
+    /**
+     * pgvector 확장 생성
+     */
+    private void initializePgVectorExtension() {
+        try {
+            log.info("pgvector 확장 확인 중...");
+            jdbcTemplate.execute("CREATE EXTENSION IF NOT EXISTS vector");
+            log.info("pgvector 확장 확인 완료");
+        } catch (Exception e) {
+            log.warn("pgvector 확장 생성 실패 (이미 존재할 수 있음): {}", e.getMessage());
+        }
+    }
+
+    /**
+     * memory_embeddings 테이블 생성
+     */
+    private void createMemoryEmbeddingsTable() {
+        try {
+            log.info("memory_embeddings 테이블 생성 중...");
+            String sql = """
+                CREATE TABLE IF NOT EXISTS memory_embeddings (
+                  id BIGSERIAL PRIMARY KEY,
+                  memory_id BIGINT NULL,
+                  user_id VARCHAR(255),
+                  memory_text TEXT NOT NULL,
+                  importance INT DEFAULT 1,
+                  created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
+                  embedding VECTOR(768) NOT NULL
+                )
+                """;
+            jdbcTemplate.execute(sql);
+            log.info("memory_embeddings 테이블 생성 완료");
+        } catch (Exception e) {
+            log.warn("memory_embeddings 테이블 생성 실패 (이미 존재할 수 있음): {}", e.getMessage());
+        }
+    }
+
+    /**
+     * 벡터 인덱스 생성 (cosine similarity)
+     */
+    private void createVectorIndex() {
+        try {
+            log.info("벡터 인덱스 생성 중...");
+            // 기존 인덱스가 있으면 삭제 후 재생성 (IF NOT EXISTS는 ivfflat에서 지원 안 함)
+            String dropIndexSql = "DROP INDEX IF EXISTS memory_embeddings_embedding_idx";
+            jdbcTemplate.execute(dropIndexSql);
+            
+            // ivfflat 인덱스 생성 (lists=100은 데이터량에 따라 조정 필요)
+            String createIndexSql = """
+                CREATE INDEX memory_embeddings_embedding_idx 
+                ON memory_embeddings USING ivfflat (embedding vector_cosine_ops) 
+                WITH (lists = 100)
+                """;
+            jdbcTemplate.execute(createIndexSql);
+            log.info("벡터 인덱스 생성 완료");
+        } catch (Exception e) {
+            log.warn("벡터 인덱스 생성 실패 (이미 존재할 수 있음): {}", e.getMessage());
+        }
+    }
+}
+
diff --git a/src/main/java/com/pandol365/dewey/domain/memory/service/EmbeddingClient.java b/src/main/java/com/pandol365/dewey/domain/memory/service/EmbeddingClient.java
index 1a44230..2598266 100644
--- a/src/main/java/com/pandol365/dewey/domain/memory/service/EmbeddingClient.java
+++ b/src/main/java/com/pandol365/dewey/domain/memory/service/EmbeddingClient.java
@@ -24,12 +24,15 @@ public class EmbeddingClient {
     @Value("${embedding.api.base-url:http://localhost:8000}")
     private String embeddingBaseUrl;
 
-    @Value("${embedding.api.path:/embed}")
+    @Value("${embedding.api.path:/embeddings}")
     private String embeddingPath;
 
+    @Value("${embedding.api.model:sentence-transformers/all-mpnet-base-v2}")
+    private String embeddingModel;
+
     /**
      * 텍스트 임베딩 생성
-     * 기대 응답 형식: { "embedding": [float, float, ...] }
+     * Infinity API 형식: 요청 { "model": "...", "input": "..." }, 응답 { "data": [{"embedding": [...]}] }
      */
     public float[] embed(String text) {
         try {
@@ -37,21 +40,38 @@ public class EmbeddingClient {
                     .scheme(extractScheme(embeddingBaseUrl))
                     .host(extractHost(embeddingBaseUrl))
                     .port(extractPort(embeddingBaseUrl))
-                    .path(embeddingPath == null ? "/embed" : embeddingPath)
+                    .path(embeddingPath == null ? "/embeddings" : embeddingPath)
                     .toUriString();
 
+            // Infinity API 요청 형식: {"model": "...", "input": "..."}
+            Map<String, Object> request = Map.of(
+                    "model", embeddingModel != null ? embeddingModel : "sentence-transformers/all-mpnet-base-v2",
+                    "input", text
+            );
+
             @SuppressWarnings("unchecked")
             Map<String, Object> resp = restTemplate.postForObject(
                     url,
-                    Map.of("text", text),
+                    request,
                     Map.class
             );
 
-            if (resp == null || !resp.containsKey("embedding")) {
-                throw new IllegalStateException("embedding field missing in response");
+            if (resp == null || !resp.containsKey("data")) {
+                throw new IllegalStateException("data field missing in response");
             }
 
-            Object embObj = resp.get("embedding");
+            Object dataObj = resp.get("data");
+            if (!(dataObj instanceof List<?> dataList) || dataList.isEmpty()) {
+                throw new IllegalStateException("data is not a non-empty list");
+            }
+
+            // data[0].embedding 추출
+            Object firstItem = dataList.get(0);
+            if (!(firstItem instanceof Map<?, ?> firstMap)) {
+                throw new IllegalStateException("data[0] is not a map");
+            }
+
+            Object embObj = firstMap.get("embedding");
             if (!(embObj instanceof List<?> list)) {
                 throw new IllegalStateException("embedding is not a list");
             }
diff --git a/src/main/resources/application.properties b/src/main/resources/application.properties
index c90fb00..122a960 100644
--- a/src/main/resources/application.properties
+++ b/src/main/resources/application.properties
@@ -17,6 +17,7 @@ spring.data.redis.host=localhost
 spring.data.redis.port=6379
 
 # Embedding service
-# all-mpnet-base-v2 768d embedding endpoint
-embedding.api.base-url=http://localhost:8000
-embedding.api.path=/embed
+# all-mpnet-base-v2 768d embedding endpoint (infinity)
+embedding.api.base-url=http://192.168.100.220:8000
+embedding.api.path=/embeddings
+embedding.api.model=sentence-transformers/all-mpnet-base-v2