diff --git a/langchain/agents/agent_toolkits/openapi/planner.py b/langchain/agents/agent_toolkits/openapi/planner.py
index b9ae8d52..bf4e1280 100644
--- a/langchain/agents/agent_toolkits/openapi/planner.py
+++ b/langchain/agents/agent_toolkits/openapi/planner.py
@@ -24,6 +24,7 @@ from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.tools import Tool
 from langchain.chains.llm import LLMChain
 from langchain.llms.openai import OpenAI
+from langchain.memory import ReadOnlySharedMemory
 from langchain.prompts import PromptTemplate
 from langchain.requests import RequestsWrapper
 from langchain.schema import BaseLanguageModel
@@ -53,7 +54,8 @@ class RequestsGetToolWithParsing(BaseRequestsTool, BaseTool):
             data = json.loads(text)
         except json.JSONDecodeError as e:
             raise e
-        response = self.requests_wrapper.get(data["url"])
+        data_params = data.get("params")
+        response = self.requests_wrapper.get(data["url"], params=data_params)
         response = response[: self.response_length]
         return self.llm_chain.predict(
             response=response, instructions=data["output_instructions"]
@@ -183,6 +185,7 @@ def create_openapi_agent(
     api_spec: ReducedOpenAPISpec,
     requests_wrapper: RequestsWrapper,
     llm: BaseLanguageModel,
+    shared_memory: Optional[ReadOnlySharedMemory] = None,
 ) -> AgentExecutor:
     """Instantiate API planner and controller for a given spec.
 
@@ -207,7 +210,7 @@ def create_openapi_agent(
         },
     )
     agent = ZeroShotAgent(
-        llm_chain=LLMChain(llm=llm, prompt=prompt),
+        llm_chain=LLMChain(llm=llm, prompt=prompt, memory=shared_memory),
         allowed_tools=[tool.name for tool in tools],
     )
     return AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
diff --git a/langchain/agents/agent_toolkits/openapi/planner_prompt.py b/langchain/agents/agent_toolkits/openapi/planner_prompt.py
index 9940a791..4db0fd8d 100644
--- a/langchain/agents/agent_toolkits/openapi/planner_prompt.py
+++ b/langchain/agents/agent_toolkits/openapi/planner_prompt.py
@@ -40,7 +40,7 @@ Here are endpoints you can use. Do not reference any of the endpoints above.
 User query: {query}
 Plan:"""
 API_PLANNER_TOOL_NAME = "api_planner"
-API_PLANNER_TOOL_DESCRIPTION = f"Can be used to generate the right API calls to assist with a user query, like {API_PLANNER_TOOL_NAME}(query). Should always be called before trying to calling the API controller."
+API_PLANNER_TOOL_DESCRIPTION = f"Can be used to generate the right API calls to assist with a user query, like {API_PLANNER_TOOL_NAME}(query). Should always be called before trying to call the API controller."
 
 # Execution.
 API_CONTROLLER_PROMPT = """You are an agent that gets a sequence of API calls and given their documentation, should execute them and return the final response.
@@ -81,7 +81,7 @@ API_CONTROLLER_TOOL_DESCRIPTION = f"Can be used to execute a plan of API calls,
 # The goal is to have an agent at the top-level (e.g. so it can recover from errors and re-plan) while
 # keeping planning (and specifically the planning prompt) simple.
 API_ORCHESTRATOR_PROMPT = """You are an agent that assists with user queries against API, things like querying information or creating resources.
-Some user queries can be resolved in a single API call though some require several API call.
+Some user queries can be resolved in a single API call, particularly if you can find appropriate params from the OpenAPI spec; though some require several API call.
 You should always plan your API calls first, and then execute the plan second.
 You should never return information without executing the api_controller tool.
 
@@ -106,12 +106,12 @@ User query: can you add some trendy stuff to my shopping cart.
 Thought: I should plan API calls first.
 Action: api_planner
 Action Input: I need to find the right API calls to add trendy items to the users shopping cart
-Observation: 1) GET /items/trending to get trending item ids
+Observation: 1) GET /items with params 'trending' is 'True' to get trending item ids
 2) GET /user to get user
 3) POST /cart to post the trending items to the user's cart
 Thought: I'm ready to execute the API calls.
 Action: api_controller
-Action Input: 1) GET /items/trending to get trending item ids
+Action Input: 1) GET /items params 'trending' is 'True' to get trending item ids
 2) GET /user to get user
 3) POST /cart to post the trending items to the user's cart
 ...
@@ -123,8 +123,12 @@ Thought: I should generate a plan to help with this query and then copy that pla
 {agent_scratchpad}"""
 
 REQUESTS_GET_TOOL_DESCRIPTION = """Use this to GET content from a website.
-Input to the tool should be a json string with 2 keys: "url" and "output_instructions".
-The value of "url" should be a string. The value of "output_instructions" should be instructions on what information to extract from the response, for example the id(s) for a resource(s) that the GET request fetches.
+Input to the tool should be a json string with 3 keys: "url", "params" and "output_instructions".
+The value of "url" should be a string. 
+The value of "params" should be a dict of the needed and available parameters from the OpenAPI spec related to the endpoint. 
+If parameters are not needed, or not available, leave it empty.
+The value of "output_instructions" should be instructions on what information to extract from the response, 
+for example the id(s) for a resource(s) that the GET request fetches.
 """
 
 PARSING_GET_PROMPT = PromptTemplate(