Add CSV and PDF tools to MCP server

app.py

@@ -23,7 +23,35 @@ def server_status() -> str:
         outputs=gr.JSON(),
         title="SQL Query Tool",
         description="Execute read-only SQL queries",
-        examples=["SELECT 1 AS one"]
+        examples=["SELECT 1 AS one"],
+        api_name="sql"
+    )
+
+    summarise_csv_interface = gr.Interface(
+        fn=summarise_csv,
+        inputs=gr.Textbox(label="CSV File Path"),
+        outputs=gr.JSON(),
+        title="CSV Summary Tool",
+        description="Analyze and summarize a CSV file",
+        examples=["sample_data/people.csv"],
+        api_name="csv"
+    )
+
+    create_pdf_interface = gr.Interface(
+        fn=create_pdf,
+        inputs=[
+            gr.JSON(label="Report Data"),
+            gr.Textbox(label="Output Path (optional)", 
+                    placeholder="Leave empty for default location"),
+            gr.Checkbox(label="Include Chart", value=True)
+        ],
+        outputs=gr.Textbox(label="Generated PDF Path"),
+        title="PDF Report Generator",
+        description="Create professional PDF reports with data and optional charts",
+        examples=[
+            [{"customer": "ACME", "order_id": 12345, "total": 999, "items": 5}, None, True]
+        ],
+        api_name="pdf"
     )
 
     # Add simple UI components

tests/test_gradio_e2e.py

@@ -46,9 +46,21 @@ def test_mcp_end_to_end(tmp_path):
         client = Client("http://127.0.0.1:7860")
         print(f"Available endpoints: {client.view_api()}")
 
-        # Test SQL tool - use the "/predict" endpoint (auto-created for the Interface)
-        result = client.predict("SELECT 1 AS one", api_name="/predict")
+        # Test SQL tool
+        result = client.predict("SELECT 1 AS one", api_name="/sql")
         assert result == [{"one": 1}]
+
+        # Test CSV tool
+        csv_result = client.predict("sample_data/people.csv", api_name="/csv") 
+        assert csv_result["row_count"] == 3
+        assert csv_result["column_count"] == 3
+        assert len(csv_result["columns"]) == 3
+
+        # Test PDF tool with minimal data
+        test_data = {"test_key": "test_value", "test_number": 42}
+        pdf_path = client.predict(test_data, None, True, api_name="/pdf")
+        assert os.path.exists(pdf_path)
+        assert os.path.getsize(pdf_path) > 1000  # Ensure PDF was created and has content
     finally:
         # Clean up
         os.kill(proc.pid, signal.SIGTERM)

tools/csv_tool.py

@@ -24,6 +24,23 @@
 
 
 def summarise_csv(path: str | Path) -> Dict[str, object]:
+    """
+    Analyze a CSV file and provide summary statistics.
+
+    Opens the CSV file using pandas and returns basic statistics including the number of rows, 
+    columns, and per-column information (name, data type, missing value count).
+
+    Args:
+        path: Path to the CSV file (must exist and have .csv extension)
+
+    Returns:
+        Dictionary with row_count, column_count, and detailed column information
+
+    Raises:
+        FileNotFoundError: If the file doesn't exist
+        ValueError: If the file doesn't have a .csv extension
+        MemoryError: If the file contains more than 1,000,000 rows
+    """
     path = Path(path)
     if not path.exists():
         raise FileNotFoundError(f"No such file: {path}")

tools/pdf_tool.py

@@ -41,6 +41,26 @@ def create_pdf(
     out_path: str | None = None,
     include_chart: bool = True,
 ) -> str:
+    """
+    Generate a professional PDF report from provided data.
+
+    Creates a PDF document with the given data formatted as a table. Optionally includes
+    a bar chart visualization of numeric values, if at least 3 numeric fields are present.
+    The PDF includes the company logo if available in the assets directory.
+
+    Args:
+        data: Dictionary containing the data to include in the report
+        out_path: Optional custom path for the generated PDF file 
+            (default: reports/report-{timestamp}.pdf)
+        include_chart: Whether to include a bar chart visualization of numeric values 
+            (default: True)
+
+    Returns:
+        Absolute path to the generated PDF file
+
+    Raises:
+        ValueError: If the data dictionary is empty
+    """
     if not data:
         raise ValueError("data cannot be empty.")