Merge pull request #6 from madebygps/main

Adds tool filtering example

Author: madebygps

README.md

@@ -48,6 +48,8 @@ Run any script with: `uv run <script_name>`
 - **basic_mcp_http.py** - MCP server with HTTP transport on port 8000
 - **basic_mcp_stdio.py** - MCP server with stdio transport for VS Code integration
 - **langchainv1_mcp_http.py** - LangChain agent with MCP integration
+- **langchainv1_mcp_github.py** - LangChain tool filtering demo with GitHub MCP (requires `GITHUB_TOKEN`)
+- **openai_agents_tool_filtering.py** - OpenAI Agents SDK tool filtering demo with Microsoft Learn MCP
 - **agentframework_mcp_learn.py** - Microsoft Agent Framework integration with MCP
 
 ## MCP Server Configuration

langchainv1_mcp_github.py

@@ -0,0 +1,108 @@
+"""LangChain MCP Tool Filtering Example
+
+Demonstrates how to filter MCP tools to create safe, focused agents.
+Shows filtering for read-only research agent using GitHub MCP server.
+"""
+
+import asyncio
+import os
+from dotenv import load_dotenv
+from rich import print as rprint
+from rich.panel import Panel
+from rich.console import Console
+import azure.identity
+from langchain.agents import create_agent
+from langchain_core.messages import HumanMessage
+from langchain_mcp_adapters.client import MultiServerMCPClient
+from langchain_openai import AzureChatOpenAI, ChatOpenAI
+from pydantic import SecretStr
+
+load_dotenv(override=True)
+
+# Configure model
+API_HOST = os.getenv("API_HOST", "github")
+if API_HOST == "azure":
+    token_provider = azure.identity.get_bearer_token_provider(
+        azure.identity.DefaultAzureCredential(),
+        "https://cognitiveservices.azure.com/.default",
+    )
+    model = AzureChatOpenAI(
+        azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        azure_deployment=os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT"],
+        api_version=os.environ["AZURE_OPENAI_VERSION"],
+        azure_ad_token_provider=token_provider,
+    )
+elif API_HOST == "github":
+    model = ChatOpenAI(
+        model=os.getenv("GITHUB_MODEL", "gpt-4o"),
+        base_url="https://models.inference.ai.azure.com",
+        api_key=SecretStr(os.environ["GITHUB_TOKEN"]),
+    )
+elif API_HOST == "ollama":
+    model = ChatOpenAI(
+        model=os.environ.get("OLLAMA_MODEL", "llama3.1"),
+        base_url=os.environ.get("OLLAMA_ENDPOINT", "http://localhost:11434/v1"),
+        api_key=SecretStr("none"),
+    )
+
+console = Console()
+
+
+async def main():
+    """Create a safe research agent with filtered read-only tools"""
+    console.print("\n[bold white on blue] LangChain Tool Filtering Demo [/bold white on blue]\n")
+    
+    console.print(Panel.fit(
+        "[bold cyan]GitHub Research Agent (Read-Only)[/bold cyan]\n"
+        "Filtered to only safe search tools",
+        border_style="cyan"
+    ))
+    
+    mcp_client = MultiServerMCPClient({
+        "github": {
+            "url": "https://api.githubcopilot.com/mcp/",
+            "transport": "streamable_http",
+            "headers": {"Authorization": f"Bearer {os.environ['GITHUB_TOKEN']}"},
+        }
+    })
+    
+    # Get all tools and show what we're filtering out
+    all_tools = await mcp_client.get_tools()
+    
+    console.print(f"[dim]Total tools available: {len(all_tools)}[/dim]\n")
+    
+    # Filter to ONLY read operations
+    safe_tool_names = ['search_repositories', 'search_code', 'search_issues']
+    filtered_tools = [t for t in all_tools if t.name in safe_tool_names]
+    
+    console.print("[bold cyan]Filtered Tools (read-only):[/bold cyan]")
+    for tool in filtered_tools:
+        console.print(f"  ✓ {tool.name}")
+    
+    # Show what was filtered out
+    blocked_tools = [t for t in all_tools if 'create' in t.name or 'update' in t.name or 'fork' in t.name]
+    if blocked_tools:
+        console.print(f"\n[dim]Blocked tools ({len(blocked_tools)}): " + ", ".join([t.name for t in blocked_tools[:5]]) + "...[/dim]")
+    
+    console.print()
+    
+    # Create agent with filtered tools
+    agent = create_agent(
+        model,
+        tools=filtered_tools,
+        prompt="You help users research GitHub repositories. Search and analyze information."
+    )
+    
+    query = "Find popular Python MCP server repositories"
+    rprint(f"[bold]Query:[/bold] {query}\n")
+    
+    try:
+        result = await agent.ainvoke({"messages": [HumanMessage(content=query)]})
+        rprint(f"[bold green]Result:[/bold green]\n{result['messages'][-1].content}\n")
+    except Exception as e:
+        rprint(f"[bold red]Error:[/bold red] {str(e)}\n")
+    
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

spanish/README.md

@@ -49,6 +49,7 @@ Ejecuta cualquier script con: `uv run <script_name>`
 - **basic_mcp_stdio.py** - MCP server con transporte stdio (útil para integración con VS Code / Copilot)
 - **langchainv1_mcp_http.py** - Agente LangChain que usa MCP tools
 - **agentframework_mcp_learn.py** - Integración con Microsoft Agent Framework y MCP
+- **langchainv1_mcp_github.py** - LangChain tool filtering demo con GitHub MCP (necesita `GITHUB_TOKEN`)
 
 ## Configuración del servidor MCP