fix: add missing 'items' attribute for MCP array parameters

This fixes an issue where MCP tools with array parameters were not working
correctly with OpenAI-compatible LLMs. The tools were missing the required
'items' attribute that specifies the type of elements in the array.

- Added _fix_array_schemas() method to recursively fix array schemas
- Updated to_openai_tool() in both mcp.py and mcp_sse.py to apply the fix
- Maintains backward compatibility by preserving existing schemas

Fixes #619

Co-authored-by: Mervin Praison <[email protected]>

Author: claude[bot]

src/praisonai-agents/praisonaiagents/mcp/mcp.py

@@ -379,6 +379,43 @@ def __iter__(self) -> Iterable[Callable]:
         """
         return iter(self._tools)
 
+    def _fix_array_schemas(self, schema):
+        """
+        Fix array schemas by adding missing 'items' attribute required by OpenAI.
+        
+        This ensures compatibility with OpenAI's function calling format which
+        requires array types to specify the type of items they contain.
+        
+        Args:
+            schema: The schema dictionary to fix
+            
+        Returns:
+            dict: The fixed schema
+        """
+        if not isinstance(schema, dict):
+            return schema
+            
+        # Create a copy to avoid modifying the original
+        fixed_schema = schema.copy()
+        
+        # Fix array types at the current level
+        if fixed_schema.get("type") == "array" and "items" not in fixed_schema:
+            # Add a default items schema for arrays without it
+            fixed_schema["items"] = {"type": "string"}
+            
+        # Recursively fix nested schemas
+        if "properties" in fixed_schema:
+            fixed_properties = {}
+            for prop_name, prop_schema in fixed_schema["properties"].items():
+                fixed_properties[prop_name] = self._fix_array_schemas(prop_schema)
+            fixed_schema["properties"] = fixed_properties
+            
+        # Fix items schema if it exists
+        if "items" in fixed_schema:
+            fixed_schema["items"] = self._fix_array_schemas(fixed_schema["items"])
+            
+        return fixed_schema
+    
     def to_openai_tool(self):
         """Convert the MCP tool to an OpenAI-compatible tool definition.
         
@@ -404,7 +441,8 @@ def to_openai_tool(self):
             # Create OpenAI tool definition
             parameters = {}
             if hasattr(tool, 'inputSchema') and tool.inputSchema:
-                parameters = tool.inputSchema
+                # Fix array schemas to include 'items' attribute
+                parameters = self._fix_array_schemas(tool.inputSchema)
             else:
                 # Create a minimal schema if none exists
                 parameters = {

src/praisonai-agents/praisonaiagents/mcp/mcp_sse.py

@@ -88,14 +88,54 @@ async def _async_call(self, **kwargs):
             logger.error(f"Error in _async_call for {self.name}: {e}")
             raise
 
+    def _fix_array_schemas(self, schema):
+        """
+        Fix array schemas by adding missing 'items' attribute required by OpenAI.
+        
+        This ensures compatibility with OpenAI's function calling format which
+        requires array types to specify the type of items they contain.
+        
+        Args:
+            schema: The schema dictionary to fix
+            
+        Returns:
+            dict: The fixed schema
+        """
+        if not isinstance(schema, dict):
+            return schema
+            
+        # Create a copy to avoid modifying the original
+        fixed_schema = schema.copy()
+        
+        # Fix array types at the current level
+        if fixed_schema.get("type") == "array" and "items" not in fixed_schema:
+            # Add a default items schema for arrays without it
+            fixed_schema["items"] = {"type": "string"}
+            
+        # Recursively fix nested schemas
+        if "properties" in fixed_schema:
+            fixed_properties = {}
+            for prop_name, prop_schema in fixed_schema["properties"].items():
+                fixed_properties[prop_name] = self._fix_array_schemas(prop_schema)
+            fixed_schema["properties"] = fixed_properties
+            
+        # Fix items schema if it exists
+        if "items" in fixed_schema:
+            fixed_schema["items"] = self._fix_array_schemas(fixed_schema["items"])
+            
+        return fixed_schema
+    
     def to_openai_tool(self):
         """Convert the tool to OpenAI format."""
+        # Fix array schemas to include 'items' attribute
+        fixed_schema = self._fix_array_schemas(self.input_schema)
+        
         return {
             "type": "function",
             "function": {
                 "name": self.name,
                 "description": self.description,
-                "parameters": self.input_schema
+                "parameters": fixed_schema
             }
         }