feat: Add a load MCP resource tool

If the user specifies use_mcp_resources=True in their MCPToolset, the agent will be able to load resources with the load_mcp_resource_tool.

Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 866539602

src/google/adk/tools/load_mcp_resource_tool.py

@@ -0,0 +1,170 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import base64
+import json
+import logging
+from typing import Any
+from typing import TYPE_CHECKING
+
+from google.genai import types
+from typing_extensions import override
+
+from ..features import FeatureName
+from ..features import is_feature_enabled
+from ..models.llm_request import LlmRequest
+from .base_tool import BaseTool
+
+if TYPE_CHECKING:
+  from mcp_toolset import McpToolset
+
+  from .tool_context import ToolContext
+
+logger = logging.getLogger("google_adk." + __name__)
+
+
+class LoadMcpResourceTool(BaseTool):
+  """A tool that loads the MCP resources and adds them to the session."""
+
+  def __init__(self, mcp_toolset: McpToolset):
+    super().__init__(
+        name="load_mcp_resource",
+        description="""Loads resources from the MCP server.
+
+NOTE: Call when you need access to resources.""",
+    )
+    self._mcp_toolset = mcp_toolset
+
+  def _get_declaration(self) -> types.FunctionDeclaration | None:
+    if is_feature_enabled(FeatureName.JSON_SCHEMA_FOR_FUNC_DECL):
+      return types.FunctionDeclaration(
+          name=self.name,
+          description=self.description,
+          parameters_json_schema={
+              "type": "object",
+              "properties": {
+                  "resource_names": {
+                      "type": "array",
+                      "items": {"type": "string"},
+                  },
+              },
+          },
+      )
+    return types.FunctionDeclaration(
+        name=self.name,
+        description=self.description,
+        parameters=types.Schema(
+            type=types.Type.OBJECT,
+            properties={
+                "resource_names": types.Schema(
+                    type=types.Type.ARRAY,
+                    items=types.Schema(
+                        type=types.Type.STRING,
+                    ),
+                )
+            },
+        ),
+    )
+
+  @override
+  async def run_async(
+      self, *, args: dict[str, Any], tool_context: ToolContext
+  ) -> Any:
+    resource_names: list[str] = args.get("resource_names", [])
+    return {
+        "resource_names": resource_names,
+        "status": (
+            "resource contents temporarily inserted and removed. to access"
+            " these resources, call load_mcp_resource tool again."
+        ),
+    }
+
+  @override
+  async def process_llm_request(
+      self, *, tool_context: ToolContext, llm_request: LlmRequest
+  ) -> None:
+    await super().process_llm_request(
+        tool_context=tool_context,
+        llm_request=llm_request,
+    )
+    await self._append_resources_to_llm_request(
+        tool_context=tool_context, llm_request=llm_request
+    )
+
+  async def _append_resources_to_llm_request(
+      self, *, tool_context: ToolContext, llm_request: LlmRequest
+  ):
+    try:
+      resource_names = await self._mcp_toolset.list_resources()
+      if resource_names:
+        llm_request.append_instructions([f"""You have a list of MCP resources:
+{json.dumps(resource_names)}
+
+When the user asks questions about any of the resources, you should call the
+`load_mcp_resource` function to load the resource. Always call load_mcp_resource
+before answering questions related to the resources.
+"""])
+    except Exception as e:
+      logger.warning("Failed to list MCP resources: %s", e)
+
+    # Attach content
+    if llm_request.contents and llm_request.contents[-1].parts:
+      function_response = llm_request.contents[-1].parts[0].function_response
+      if function_response and function_response.name == self.name:
+        response = function_response.response or {}
+        resource_names = response.get("resource_names", [])
+        for resource_name in resource_names:
+          try:
+            contents = await self._mcp_toolset.read_resource(resource_name)
+
+            for content in contents:
+              part = self._mcp_content_to_part(content, resource_name)
+              llm_request.contents.append(
+                  types.Content(
+                      role="user",
+                      parts=[
+                          types.Part.from_text(
+                              text=f"Resource {resource_name} is:"
+                          ),
+                          part,
+                      ],
+                  )
+              )
+          except Exception as e:
+            logger.warning(
+                "Failed to read MCP resource '%s': %s", resource_name, e
+            )
+            continue
+
+  def _mcp_content_to_part(
+      self, content: Any, resource_name: str
+  ) -> types.Part:
+    if hasattr(content, "text") and content.text is not None:
+      return types.Part.from_text(text=content.text)
+    elif hasattr(content, "blob") and content.blob is not None:
+      try:
+        data = base64.b64decode(content.blob)
+        # Basic check for mime type or default
+        mime_type = content.mimeType or "application/octet-stream"
+        return types.Part.from_bytes(data=data, mime_type=mime_type)
+      except Exception:
+        return types.Part.from_text(
+            text=f"[Binary content for {resource_name} could not be decoded]"
+        )
+    else:
+      return types.Part.from_text(
+          text=f"[Unknown content type for {resource_name}]"
+      )

src/google/adk/tools/mcp_tool/mcp_toolset.py

@@ -16,7 +16,6 @@ from __future__ import annotations
 
 import asyncio
 import base64
-import json
 import logging
 import sys
 from typing import Any
@@ -44,8 +43,10 @@ from ...auth.auth_tool import AuthConfig
 from ..base_tool import BaseTool
 from ..base_toolset import BaseToolset
 from ..base_toolset import ToolPredicate
+from ..load_mcp_resource_tool import LoadMcpResourceTool
 from ..tool_configs import BaseToolConfig
 from ..tool_configs import ToolArgsConfig
+from ..tool_context import ToolContext
 from .mcp_session_manager import MCPSessionManager
 from .mcp_session_manager import retry_on_errors
 from .mcp_session_manager import SseConnectionParams
@@ -112,6 +113,7 @@ class McpToolset(BaseToolset):
       progress_callback: Optional[
           Union[ProgressFnT, ProgressCallbackFactory]
       ] = None,
+      use_mcp_resources: Optional[bool] = False,
   ):
     """Initializes the McpToolset.
 
@@ -148,7 +150,11 @@ class McpToolset(BaseToolset):
           progress handling logic and access/modify session state via the
           CallbackContext. The **kwargs parameter allows for future
           extensibility.
+      use_mcp_resources: Whether the agent should have access to MCP resources.
+        This will add a `load_mcp_resource` tool to the toolset and include
+        available resources in the agent context. Defaults to False.
     """
+
     super().__init__(tool_filter=tool_filter, tool_name_prefix=tool_name_prefix)
 
     if not connection_params:
@@ -177,6 +183,7 @@ class McpToolset(BaseToolset):
         if auth_scheme
         else None
     )
+    self._use_mcp_resources = use_mcp_resources
 
   def _get_auth_headers(self) -> Optional[Dict[str, str]]:
     """Build authentication headers from exchanged credential.
@@ -317,6 +324,13 @@ class McpToolset(BaseToolset):
 
       if self._is_tool_selected(mcp_tool, readonly_context):
         tools.append(mcp_tool)
+
+    if self._use_mcp_resources:
+      load_resource_tool = LoadMcpResourceTool(
+          mcp_toolset=self,
+      )
+      tools.append(load_resource_tool)
+
     return tools
 
   async def read_resource(
@@ -415,6 +429,7 @@ class McpToolset(BaseToolset):
         tool_name_prefix=mcp_toolset_config.tool_name_prefix,
         auth_scheme=mcp_toolset_config.auth_scheme,
         auth_credential=mcp_toolset_config.auth_credential,
+        use_mcp_resources=mcp_toolset_config.use_mcp_resources,
     )
 
 
@@ -451,6 +466,8 @@ class McpToolsetConfig(BaseToolConfig):
 
   auth_credential: Optional[AuthCredential] = None
 
+  use_mcp_resources: bool = False
+
   @model_validator(mode="after")
   def _check_only_one_params_field(self):
     param_fields = [