[feat] new tools for peeking and DLT, update readme

README.md

@@ -74,16 +74,51 @@ The following MCP tools are available:
 2. **list_jobs()** - List all Databricks jobs in your workspace
 3. **get_job_status(job_id: int)** - Get the status of a specific Databricks job by ID
 4. **get_job_details(job_id: int)** - Get detailed information about a specific Databricks job
+5. **preview_table(table_name: str, limit: int = 10)** - Preview rows from a Delta table
+6. **search_workspace(path: str = "/")** - List objects in a Databricks workspace path
+7. **list_pipelines()** - List Delta Live Tables pipelines
 
-## Example Usage with LLMs
+## Example Prompts for New Functions
+
+You can ask your LLM to use these tools in various ways. Here are some example prompts for each available function:
+
+### 1. `run_sql_query(sql: str)`
+- "Run the SQL: `SELECT count(*) FROM users`"
+- "What is the total revenue in the `sales` table?"
+- "Give me the earliest and latest order dates in the orders table."
+
+### 2. `list_jobs()`
+- "List all Databricks jobs in my workspace."
+- "What jobs are currently available to run?"
+
+### 3. `get_job_status(job_id: int)`
+- "Show me the run status for job 9876."
+- "Did job 123 finish successfully?"
+- "How many times has job 222 failed?"
+
+### 4. `get_job_details(job_id: int)`
+- "What tasks are included in job 1001?"
+- "Give me the details for job 345."
+
+### 5. `preview_table(table_name: str, limit: int = 10)`
+- "Preview the top 5 rows in the `customers` table."
+- "Show 10 records from table `events`."
+- "What data is in the `users_activity` table?"
+
+### 6. `search_workspace(path: str = "/")`
+- "List all folders in the workspace root."
+- "What notebooks are in `/Shared/Analytics`?"
+- "Show me all files in `/Users/janedoe`."
+
+### 7. `list_pipelines()`
+- "List all Delta Live Tables pipelines."
+- "Which DLT pipelines are available in my environment?"
+
+---
+
+Feel free to adapt these prompts to your needs or combine them for more complex workflows!
 
-When used with LLMs that support the MCP protocol, this server enables natural language interaction with your Databricks environment:
 
-- "Show me all tables in the database"
-- "Run a query to count records in the customer table"
-- "List all my Databricks jobs"
-- "Check the status of job #123"
-- "Show me details about job #456"
 
 ## Troubleshooting
 

main.py

@@ -209,5 +209,41 @@ def get_job_details(job_id: int) -> str:
     except Exception as e:
         return f"Error getting job details: {str(e)}"
 
+@mcp.tool()
+def preview_table(table_name: str, limit: int = 10) -> str:
+    """Preview rows from a Delta table"""
+    sql = f"SELECT * FROM {table_name} LIMIT {limit}"
+    return run_sql_query(sql)
+
+@mcp.tool()
+def search_workspace(path: str = "/") -> str:
+    """List objects in a Databricks workspace path"""
+    try:
+        response = databricks_api_request(f"workspace/list?path={path}")
+        objects = response.get("objects", [])
+        if not objects:
+            return f"No objects found at path: {path}"
+        table = "| Path | Type |\n| ---- | ---- |\n"
+        for obj in objects:
+            table += f"| {obj.get('path')} | {obj.get('object_type')} |\n"
+        return table
+    except Exception as e:
+        return f"Error listing workspace objects: {str(e)}"
+
+@mcp.tool()
+def list_pipelines() -> str:
+    """List Delta Live Tables pipelines"""
+    try:
+        response = databricks_api_request("pipelines")
+        pipelines = response.get("statuses", [])
+        if not pipelines:
+            return "No DLT pipelines found."
+        table = "| Pipeline ID | Name | State |\n| ------------ | ---- | ------ |\n"
+        for p in pipelines:
+            table += f"| {p.get('pipeline_id')} | {p.get('name')} | {p.get('state')} |\n"
+        return table
+    except Exception as e:
+        return f"Error listing DLT pipelines: {str(e)}"
+
 if __name__ == "__main__":
     mcp.run()