fix: mcp server lint errors

cognee-mcp/src/__init__.py

@@ -1,5 +1,6 @@
 from .server import mcp
 
+
 def main():
     """Main entry point for the package."""
     mcp.run(transport="stdio")

cognee-mcp/src/client.py

@@ -4,9 +4,9 @@ from mcp.client.stdio import stdio_client
 
 # Create server parameters for stdio connection
 server_params = StdioServerParameters(
-    command="mcp", # Executable
-    args=["run", "src/server.py"], # Optional command line arguments
-    env=None # Optional environment variables
+    command="mcp",  # Executable
+    args=["run", "src/server.py"],  # Optional command line arguments
+    env=None,  # Optional environment variables
 )
 
 text = """
@@ -27,6 +27,7 @@ brain, that can ‘learn’ from available data and make increasingly
 more accurate classifications or predictions over time.
 """
 
+
 async def run():
     async with stdio_client(server_params) as (read, write):
         async with ClientSession(read, write, timedelta(minutes=3)) as session:
@@ -37,6 +38,8 @@ async def run():
 
             print(f"Cognify result: {toolResult}")
 
+
 if __name__ == "__main__":
     import asyncio
+
     asyncio.run(run())

cognee-mcp/src/server.py

@@ -1,6 +1,7 @@
 import os
 import cognee
 import importlib.util
+
 # from PIL import Image as PILImage
 from mcp.server.fastmcp import FastMCP
 from cognee.api.v1.search import SearchType
@@ -8,6 +9,7 @@ from cognee.shared.data_models import KnowledgeGraph
 
 mcp = FastMCP("cognee", timeout=120000)
 
+
 @mcp.tool()
 async def cognify(text: str, graph_model_file: str = None, graph_model_name: str = None) -> str:
     """Build knowledge graph from the input text"""
@@ -19,9 +21,9 @@ async def cognify(text: str, graph_model_file: str = None, graph_model_name: str
     await cognee.add(text)
 
     try:
-      await cognee.cognify(graph_model=graph_model)
+        await cognee.cognify(graph_model=graph_model)
     except Exception as e:
-      raise ValueError(f"Failed to cognify: {str(e)}")
+        raise ValueError(f"Failed to cognify: {str(e)}")
 
     return "Ingested"
 
@@ -57,7 +59,6 @@ async def prune() -> str:
 #       raise ValueError(f"Failed to create visualization: {str(e)}")
 
 
-
 def node_to_string(node):
     node_data = ", ".join(
         [f'{key}: "{value}"' for key, value in node.items() if key in ["id", "name"]]