Fix tool calling issue when using AWS Bedrock Nova models (#134)

Author: StreetLamb

examples/mcp_basic_bedrock_agent/README.md

@@ -19,7 +19,7 @@ Configuration Options
 2. Via your AWS config file (`~/.aws/config` and/or `~/.aws/credentials`)
 
 Optional:
-- `default_model`: Defaults to `amazon.nova-lite-v1:0` but can be customized in your config.
+- `default_model`: Defaults to `us.amazon.nova-lite-v1:0` but can be customized in your config. For more info see: https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles-support.html
 - `profile`: Select which AWS profile should be used.
 
 ## Running the Agent

examples/mcp_basic_bedrock_agent/mcp_agent.config.yaml

@@ -18,5 +18,4 @@ mcp:
 
 bedrock:
   # Secrets (API keys, etc.) are stored in an mcp_agent.secrets.yaml file which can be gitignored
-  #  default_model: "amazon.nova-lite-v1:0"
-  default_model: "anthropic.claude-3-haiku-20240307-v1:0"
+  default_model: "us.amazon.nova-lite-v1:0"

src/mcp_agent/agents/agent.py

@@ -173,7 +173,11 @@ async def list_tools(self) -> ListToolsResult:
             Tool(
                 name=HUMAN_INPUT_TOOL_NAME,
                 description=human_input_tool.description,
-                inputSchema=human_input_tool.parameters,
+                inputSchema={
+                    "type": "object",
+                    "properties": {"request": HumanInputRequest.model_json_schema()},
+                    "required": ["request"],
+                },
             )
         )
 

src/mcp_agent/mcp/mcp_aggregator.py

@@ -31,7 +31,7 @@
     __name__
 )  # This will be replaced per-instance when agent_name is available
 
-SEP = "-"
+SEP = "_"
 
 # Define type variables for the generalized method
 T = TypeVar("T")

src/mcp_agent/workflows/llm/augmented_llm_bedrock.py

@@ -55,7 +55,7 @@ def __init__(self, *args, **kwargs):
             intelligencePriority=0.3,
         )
         # Get default model from config if available
-        default_model = "amazon.nova-lite-v1:0"  # Fallback default
+        default_model = "us.amazon.nova-lite-v1:0"  # Fallback default
 
         if self.context.config.bedrock:
             if hasattr(self.context.config.bedrock, "default_model"):
@@ -296,7 +296,7 @@ async def generate_structured(
         client = instructor.from_bedrock(self.bedrock_client)
 
         params = self.get_request_params(request_params)
-        model = await self.select_model(params)
+        model = await self.select_model(params) or "us.amazon.nova-lite-v1:0"
 
         # Extract structured data from natural language
         structured_response = client.chat.completions.create(