diff --git a/llama_toolchain/agentic_system/client.py b/llama_toolchain/agentic_system/client.py
index fadb78182..0120de44e 100644
--- a/llama_toolchain/agentic_system/client.py
+++ b/llama_toolchain/agentic_system/client.py
@@ -16,6 +16,7 @@ from pydantic import BaseModel
 from termcolor import cprint
 
 from llama_models.llama3.api.datatypes import *  # noqa: F403
+from llama_toolchain.common.deployment_types import RestAPIExecutionConfig
 from llama_toolchain.core.datatypes import RemoteProviderConfig
 
 from .api import *  # noqa: F403
@@ -134,8 +135,21 @@ async def run_main(host: str, port: int):
     api = AgenticSystemClient(f"http://{host}:{port}")
 
     tool_definitions = [
-        BraveSearchToolDefinition(),
-        WolframAlphaToolDefinition(),
+        BraveSearchToolDefinition(
+            remote_execution=RestAPIExecutionConfig(
+                url=URL(uri="https://api.bing.microsoft.com/v7.0/search"),
+                method=RestAPIMethod.GET,
+                headers={
+                    "Ocp-Apim-Subscription-Key": "2259b3f9e0cb4fc9b968bb3b02ab13e7"
+                },
+                params={
+                    "count": 3,
+                    "textDecorations": True,
+                    "textFormat": "HTML",
+                },
+            )
+        ),
+        # WolframAlphaToolDefinition(),
         CodeInterpreterToolDefinition(),
     ]
     tool_definitions += [
diff --git a/llama_toolchain/agentic_system/meta_reference/agentic_system.py b/llama_toolchain/agentic_system/meta_reference/agentic_system.py
index 09fbfdde5..79d20fd26 100644
--- a/llama_toolchain/agentic_system/meta_reference/agentic_system.py
+++ b/llama_toolchain/agentic_system/meta_reference/agentic_system.py
@@ -18,6 +18,7 @@ from llama_toolchain.tools.builtin import (
     BraveSearchTool,
     CodeInterpreterTool,
     PhotogenTool,
+    RemoteSearchTool,
     WolframAlphaTool,
 )
 from llama_toolchain.tools.safety import with_safety
@@ -63,10 +64,13 @@ class MetaReferenceAgenticSystemImpl(AgenticSystem):
                     raise ValueError("Wolfram API key not defined in config")
                 tool = WolframAlphaTool(key)
             elif isinstance(tool_defn, BraveSearchToolDefinition):
-                key = self.config.brave_search_api_key
-                if not key:
-                    raise ValueError("Brave API key not defined in config")
-                tool = BraveSearchTool(key)
+                if tool_defn.remote_execution is not None:
+                    tool = RemoteSearchTool(tool_defn.remote_execution)
+                else:
+                    key = self.config.brave_search_api_key
+                    if not key:
+                        raise ValueError("Brave API key not defined in config")
+                    tool = BraveSearchTool(key)
             elif isinstance(tool_defn, CodeInterpreterToolDefinition):
                 tool = CodeInterpreterTool()
             elif isinstance(tool_defn, PhotogenToolDefinition):
diff --git a/llama_toolchain/common/deployment_types.py b/llama_toolchain/common/deployment_types.py
index 8b67eff0d..af05aaae4 100644
--- a/llama_toolchain/common/deployment_types.py
+++ b/llama_toolchain/common/deployment_types.py
@@ -5,7 +5,7 @@
 # the root directory of this source tree.
 
 from enum import Enum
-from typing import Dict, Optional
+from typing import Any, Dict, Optional
 
 from llama_models.llama3.api.datatypes import URL
 
@@ -26,6 +26,6 @@ class RestAPIMethod(Enum):
 class RestAPIExecutionConfig(BaseModel):
     url: URL
     method: RestAPIMethod
-    params: Optional[Dict[str, str]] = None
-    headers: Optional[Dict[str, str]] = None
-    body: Optional[Dict[str, str]] = None
+    params: Optional[Dict[str, Any]] = None
+    headers: Optional[Dict[str, Any]] = None
+    body: Optional[Dict[str, Any]] = None
diff --git a/llama_toolchain/inference/client.py b/llama_toolchain/inference/client.py
index 5ba9314bc..1e1dcb8c0 100644
--- a/llama_toolchain/inference/client.py
+++ b/llama_toolchain/inference/client.py
@@ -86,6 +86,14 @@ class InferenceClient(Inference):
 
 async def run_main(host: str, port: int, stream: bool):
     client = InferenceClient(f"http://{host}:{port}")
+    # from llama_toolchain.inference.meta_reference import get_provider_impl
+    # from .meta_reference.config import MetaReferenceImplConfig
+
+    # config = MetaReferenceImplConfig(
+    #     model="Meta-Llama3.1-8B-Instruct",
+    #     max_seq_len=4096,
+    # )
+    # client = await get_provider_impl(config, {})
 
     message = UserMessage(content="hello world, troll me in two-paragraphs about 42")
     cprint(f"User>{message.content}", "green")
diff --git a/llama_toolchain/tools/builtin.py b/llama_toolchain/tools/builtin.py
index 3a53e2e26..1792fde57 100644
--- a/llama_toolchain/tools/builtin.py
+++ b/llama_toolchain/tools/builtin.py
@@ -14,6 +14,8 @@ from typing import List, Optional
 import requests
 from termcolor import cprint
 
+from llama_toolchain.common.deployment_types import RestAPIExecutionConfig
+
 from .ipython_tool.code_execution import (
     CodeExecutionContext,
     CodeExecutionRequest,
@@ -83,6 +85,47 @@ class PhotogenTool(SingleMessageBuiltinTool):
         raise NotImplementedError()
 
 
+class RemoteSearchTool(SingleMessageBuiltinTool):
+    def __init__(self, config: RestAPIExecutionConfig) -> None:
+        self.config = config
+
+    def get_name(self) -> str:
+        return BuiltinTool.brave_search.value
+
+    async def run_impl(self, query: str) -> str:
+        params = self.config.params.copy()
+        params["q"] = query
+        response = requests.get(
+            url=self.config.url,
+            params=params,
+            headers=self.config.headers,
+        )
+        response.raise_for_status()
+        clean = self._clean_response(response.json())
+        return json.dumps(clean)
+
+    def _clean_response(self, search_response):
+        clean_response = []
+        query = search_response["queryContext"]["originalQuery"]
+        if "webPages" in search_response:
+            pages = search_response["webPages"]["value"]
+            for p in pages:
+                selected_keys = {"name", "url", "snippet"}
+                clean_response.append(
+                    {k: v for k, v in p.items() if k in selected_keys}
+                )
+        if "news" in search_response:
+            clean_news = []
+            news = search_response["news"]["value"]
+            for n in news:
+                selected_keys = {"name", "url", "description"}
+                clean_news.append({k: v for k, v in n.items() if k in selected_keys})
+
+            clean_response.append(clean_news)
+
+        return {"query": query, "top_k": clean_response}
+
+
 class BraveSearchTool(SingleMessageBuiltinTool):
     def __init__(self, api_key: str) -> None:
         self.api_key = api_key