Merge pull request #429 from MervinPraison/develop

Add MCP integration for stock price retrieval

Author: MervinPraison

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "PraisonAI"
-version = "2.0.80"
+version = "2.0.81"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
 readme = "README.md"
 license = ""
@@ -12,7 +12,7 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=0.0.65",
+    "praisonaiagents>=0.0.67",
     "python-dotenv>=0.19.0",
     "instructor>=1.3.3",
     "PyYAML>=6.0",
@@ -102,7 +102,7 @@ python = ">=3.10,<3.13"
 rich = ">=13.7"
 markdown = ">=3.5"
 pyparsing = ">=3.0.0"
-praisonaiagents = ">=0.0.65"
+praisonaiagents = ">=0.0.67"
 python-dotenv = ">=0.19.0"
 instructor = ">=1.3.3"
 PyYAML = ">=6.0"

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

@@ -0,0 +1,13 @@
+from praisonaiagents import Agent, MCP
+
+agent = Agent(
+    instructions="""You are a helpful assistant that can check stock prices and perform other tasks.
+    Use the available tools when relevant to answer user questions.""",
+    llm="gpt-4o-mini",
+    tools=MCP(
+        command="/Users/praison/miniconda3/envs/mcp/bin/python",
+        args=["/Users/praison/stockprice/app.py"]
+    )
+)
+
+agent.start("What is the stock price of Tesla?")

src/praisonai-agents/mcp-agents.py

@@ -0,0 +1,10 @@
+from praisonaiagents import Agent, MCP
+
+agent = Agent(
+    instructions="""You are a helpful assistant that can check stock prices and perform other tasks.
+    Use the available tools when relevant to answer user questions.""",
+    llm="gpt-4o-mini",
+    tools = MCP("/Users/praison/miniconda3/envs/mcp/bin/python /Users/praison/stockprice/app.py")
+)
+
+agent.start("What is the stock price of Tesla?")

src/praisonai-agents/mcp-basic.py

@@ -0,0 +1,61 @@
+import asyncio
+from praisonaiagents import Agent
+from mcp import ClientSession, StdioServerParameters
+from mcp.client.stdio import stdio_client
+
+# Define server configuration - pointing to your stock price app
+server_params = StdioServerParameters(
+    command="/Users/praison/miniconda3/envs/mcp/bin/python",
+    args=[
+        "/Users/praison/stockprice/app.py",
+    ],
+)
+
+# Function to get stock price using MCP
+async def get_stock_price(symbol):
+    # Start server and connect client
+    async with stdio_client(server_params) as (read, write):
+        async with ClientSession(read, write) as session:
+            # Initialize the connection
+            await session.initialize()
+            
+            # Get tools
+            tools_result = await session.list_tools()
+            tools = tools_result.tools
+            print(f"Available tools: {[tool.name for tool in tools]}")
+            
+            # Find a tool that can get stock prices
+            # Assuming there's a tool like "get_stock_price" or similar
+            stock_tool = None
+            for tool in tools:
+                if "stock" in tool.name.lower() or "price" in tool.name.lower():
+                    stock_tool = tool
+                    break
+            
+            if stock_tool:
+                print(f"Using tool: {stock_tool.name}")
+                # Call the tool with the stock symbol
+                result = await session.call_tool(
+                    stock_tool.name, 
+                    arguments={"ticker": symbol}
+                )
+                return result
+            else:
+                return "No suitable stock price tool found"
+
+# Create a custom tool for the agent
+def stock_price_tool(symbol: str) -> str:
+    """Get the current stock price for a given symbol"""
+    # Run the async function to get the stock price
+    result = asyncio.run(get_stock_price(symbol))
+    return f"Stock price for {symbol}: {result}"
+
+# Create agent with the stock price tool
+agent = Agent(
+    instructions="You are a helpful assistant that can check stock prices. When asked about stock prices, use the stock_price_tool.",
+    llm="gpt-4o-mini",
+    tools=[stock_price_tool]
+)
+
+# Start the agent
+agent.start("What is the stock price of Tesla?")

src/praisonai-agents/mcp-multiagents.py

@@ -0,0 +1,23 @@
+from praisonaiagents import Agent, MCP
+import os
+stock_agent = Agent(
+    instructions="""You are a helpful assistant that can check stock prices and perform other tasks.
+    Use the available tools when relevant to answer user questions.""",
+    llm="gpt-4o-mini",
+    tools=MCP(
+        command="/Users/praison/miniconda3/envs/mcp/bin/python",
+        args=["/Users/praison/stockprice/app.py"]
+    )
+)
+
+brave_api_key = os.getenv("BRAVE_API_KEY")
+
+search_agent = Agent(
+    instructions="""You are a helpful assistant that can search the web for information.
+    Use the available tools when relevant to answer user questions.""",
+    llm="gpt-4o-mini",
+    tools=MCP(f'npx -y @smithery/cli@latest install @smithery-ai/brave-search --client claude --config "{{\\\"braveApiKey\\\":\\\"{brave_api_key}\\\"}}"')
+)
+
+stock_agent.start("What is the stock price of Tesla?")
+search_agent.start("Search more information about Praison AI")

src/praisonai-agents/mcp-npx-airbnb-agent-direct.py

@@ -0,0 +1,18 @@
+from praisonaiagents import Agent
+
+import npx_mcp_wrapper_main
+
+search_agent = Agent(
+    instructions="""You help book apartments on Airbnb.""",
+    llm="gpt-4o-mini",
+    tools=npx_mcp_wrapper_main.MCP(
+        command="npx",
+        args=[
+            "-y",
+            "@openbnb/mcp-server-airbnb",
+            "--ignore-robots-txt",
+        ]
+    )
+)
+
+search_agent.start("I want to book an apartment in Paris for 2 nights. 03/28 - 03/30 for 2 adults")

src/praisonai-agents/mcp-npx-airbnb-stockprice.py

@@ -0,0 +1,25 @@
+from praisonaiagents import Agent, MCP
+
+search_agent = Agent(
+    instructions="""You help book apartments on Airbnb.""",
+    llm="gpt-4o-mini",
+    tools=MCP(
+        command="npx",
+        args=[
+            "-y",
+            "@openbnb/mcp-server-airbnb",
+            "--ignore-robots-txt",
+        ]
+    )
+)
+
+search_agent.start("I want to book an apartment in Paris for 2 nights. 03/28 - 03/30 for 2 adults")
+
+agent = Agent(
+    instructions="""You are a helpful assistant that can check stock prices and perform other tasks.
+    Use the available tools when relevant to answer user questions.""",
+    llm="gpt-4o-mini",
+    tools = MCP("/Users/praison/miniconda3/envs/mcp/bin/python /Users/praison/stockprice/app.py")
+)
+
+agent.start("What is the stock price of Tesla?")

src/praisonai-agents/mcp-npx-airbnb.py

@@ -0,0 +1,16 @@
+from praisonaiagents import Agent, MCP
+
+search_agent = Agent(
+    instructions="""You help book apartments on Airbnb.""",
+    llm="gpt-4o-mini",
+    tools=MCP(
+        command="npx",
+        args=[
+            "-y",
+            "@openbnb/mcp-server-airbnb",
+            "--ignore-robots-txt",
+        ]
+    )
+)
+
+search_agent.start("I want to book an apartment in Paris for 2 nights. 03/28 - 03/30 for 2 adults")

src/praisonai-agents/mcp-npx-brave.py

@@ -0,0 +1,24 @@
+from praisonaiagents import Agent, MCP
+
+search_agent = Agent(
+    instructions="""You are a helpful assistant that can search the web for information.
+    Use the available tools when relevant to answer user questions.""",
+    llm="gpt-4o-mini",
+    tools=MCP(
+        command="npx",
+        args=[
+            "-y", 
+            "@smithery/cli@latest", 
+            "install", 
+            "@smithery-ai/brave-search", 
+            "--client", 
+            "claude", 
+            "--config", 
+            '{"braveApiKey":"BSANfDaqLKO9wq7e08mrPth9ZlJvKtc"}'
+        ],
+        timeout=30,  # 3 minutes for brave-search
+        debug=True    # Enable detailed logging
+    )
+)
+
+search_agent.start("Search more information about Praison AI")

src/praisonai-agents/mcp_airbnb_client_direct.py

@@ -0,0 +1,67 @@
+from google import genai
+from google.genai import types
+from mcp import ClientSession, StdioServerParameters
+from mcp.client.stdio import stdio_client
+import os
+
+client = genai.Client(
+    api_key=os.getenv("GEMINI_API_KEY")
+)  # Replace with your actual API key setup
+
+
+# Create server parameters for stdio connection
+server_params = StdioServerParameters(
+    command="npx",  # Executable
+    args=[
+        "-y",
+        "@openbnb/mcp-server-airbnb",
+        "--ignore-robots-txt",
+    ],  # Optional command line arguments
+    env=None,  # Optional environment variables
+)
+
+async def run():
+    async with stdio_client(server_params) as (read, write):
+        async with ClientSession(
+            read,
+            write,
+        ) as session:
+            prompt = "I want to book an apartment in Paris for 2 nights. 03/28 - 03/30"
+            # Initialize the connection
+            await session.initialize()
+            
+            # Get tools from MCP session and convert to Gemini Tool objects
+            mcp_tools = await session.list_tools()
+            tools = types.Tool(function_declarations=[
+                {
+                    "name": tool.name,
+                    "description": tool.description,
+                    "parameters": tool.inputSchema,
+                }
+                for tool in mcp_tools.tools
+            ])
+            
+            # Send request with function declarations
+            response = client.models.generate_content(
+                model="gemini-2.0-flash",  # Or your preferred model supporting function calling
+                contents=prompt,
+                config=types.GenerateContentConfig(
+                    temperature=0.7,
+                    tools=[tools],
+                ),  # Example other config
+            )
+        # Check for a function call
+        if response.candidates[0].content.parts[0].function_call:
+            function_call = response.candidates[0].content.parts[0].function_call
+            print(f"Function to call: {function_call.name}")
+            print(f"Arguments: {function_call.args}")
+            # In a real app, you would call your function here:
+            # result = await session.call_tool(function_call.args, arguments=function_call.args)
+            # sent new request with function call
+        else:
+            print("No function call found in the response.")
+            print(response.text)
+            
+if __name__ == "__main__":
+    import asyncio
+    asyncio.run(run())