fix: switch FastAPI routes to Pydantic body models for MCP tools/call

The plan's route signatures used query parameters, which worked for direct
HTTP callers and unit tests, but fastapi-mcp's HTTP transport passes
tools/call arguments as a JSON body. dict-typed parameters like
spark_conf arrived as a string and the route returned 422.

Refactor each route to take a single Pydantic body model (saved in
spark_executor/tools/requests.py). Underlying tool functions unchanged.

Integration tests in tests/integration/test_mcp_routes.py now exercise
the full body-based roundtrip (save_connection with spark_conf, prepare
→ list → get, list_connections with empty body).

spark_executor/tools/requests.py

@@ -0,0 +1,50 @@
+# coding=utf-8
+"""
+@Time   :2026/6/24
+@Author :tao.chen
+
+Pydantic request models for the FastAPI route layer. The underlying tool
+functions in tools/*.py still take keyword arguments; these models exist only
+so fastapi-mcp can call the routes via tools/call (which sends args as a
+JSON body) without 422-ing on dict-typed parameters like spark_conf.
+"""
+from pydantic import BaseModel, Field
+
+
+class EmptyRequest(BaseModel):
+    """Used for tools that take no arguments (list_connections, list_pending_jobs)."""
+    pass
+
+
+class SaveConnectionRequest(BaseModel):
+    name: str
+    master: str
+    deploy_mode: str = "cluster"
+    yarn_rm_url: str | None = None
+    spark_conf: dict[str, str] | None = None
+
+
+class PrepareSubmitJobRequest(BaseModel):
+    connection: str
+    script_path: str
+    queue: str = "default"
+    executor_memory: str = "4G"
+    executor_cores: int = 2
+    num_executors: int = 2
+
+
+class PendingIdRequest(BaseModel):
+    pending_id: str
+
+
+class JobIdRequest(BaseModel):
+    job_id: str
+
+
+class GetJobLogsRequest(BaseModel):
+    job_id: str
+    tail_chars: int = 5000
+
+
+class ConnectionNameRequest(BaseModel):
+    name: str