diff --git a/docker-compose.yml b/docker-compose.yml
index 9a27022..0a48d9a 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -15,12 +15,12 @@
 #   http://localhost:8000/spark-executor-mcp   (initialize -> tools/list -> tools/call)
 
 services:
-  spark-executor-mcp:
+  mcp-server:
     build:
       context: .
       dockerfile: Dockerfile
-    image: spark-executor-mcp:latest
-    container_name: spark-executor-mcp
+    image: mcp-server:latest
+    container_name: mcp-tools
 
     restart: unless-stopped
 
@@ -48,15 +48,6 @@ services:
       # Read-only so the running container cannot mutate cluster config.
       - ./hadoop-conf:/etc/hadoop/conf:ro
 
-    healthcheck:
-      # The MCP endpoint requires an initialize handshake for real liveness;
-      # /openapi.json (the main app's spec) is a cheap proxy for "process up".
-      # Replace with a /health route once added to main.py (see note below).
-      test: ["CMD", "python", "-c", "import httpx; httpx.get('http://localhost:8000/openapi.json', timeout=5).raise_for_status()"]
-      interval: 30s
-      timeout: 5s
-      retries: 3
-      start_period: 15s
 
     # No resource limits — spark-submit talks to YARN, which does the actual
     # heavy lifting. The MCP server itself is lightweight (FastAPI + httpx).