diff --git a/README.md b/README.md
index f4833b9..2e789ca 100644
--- a/README.md
+++ b/README.md
@@ -202,10 +202,10 @@ This project includes example agents in the [`agents/`](agents/) directory that
 
 | File | Description |
 | ---- | ----------- |
-| [agents/agentframework_learn.py](agents/agentframework_learn.py) | Microsoft Agent Framework integration with MCP |
 | [agents/agentframework_http.py](agents/agentframework_http.py) | Microsoft Agent Framework integration with local Expenses MCP server |
-| [agents/langchainv1_http.py](agents/langchainv1_http.py) | LangChain agent with MCP integration |
-| [agents/langchainv1_github.py](agents/langchainv1_github.py) | LangChain tool filtering demo with GitHub MCP (requires `GITHUB_TOKEN`) |
+| [agents/agentframework_learn.py](agents/agentframework_learn.py) | Microsoft Agent Framework integration with remote Learn MCP server |
+| [agents/langchainv1_http.py](agents/langchainv1_http.py) | LangChain agent with local Expenses MCP server |
+| [agents/langchainv1_github.py](agents/langchainv1_github.py) | LangChain tool-filtering agent with remote GitHub MCP (requires `GITHUB_TOKEN`) |
 
 **To run an agent:**
 
diff --git a/agents/agentframework_http.py b/agents/agentframework_http.py
index ba36463..33c3dd8 100644
--- a/agents/agentframework_http.py
+++ b/agents/agentframework_http.py
@@ -3,10 +3,9 @@
 import os
 from datetime import datetime
 
-from agent_framework import ChatAgent, MCPStreamableHTTPTool
-from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework import Agent, MCPStreamableHTTPTool
 from agent_framework.openai import OpenAIChatClient
-from azure.identity import DefaultAzureCredential
+from azure.identity.aio import DefaultAzureCredential, get_bearer_token_provider
 from dotenv import load_dotenv
 from rich import print
 from rich.logging import RichHandler
@@ -26,19 +25,21 @@
 
 # Configure chat client based on API_HOST
 API_HOST = os.getenv("API_HOST", "github")
+async_credential = None
 
 if API_HOST == "azure":
-    client = AzureOpenAIChatClient(
-        credential=DefaultAzureCredential(),
-        deployment_name=os.environ.get("AZURE_OPENAI_CHAT_DEPLOYMENT"),
-        endpoint=os.environ.get("AZURE_OPENAI_ENDPOINT"),
-        api_version=os.environ.get("AZURE_OPENAI_VERSION"),
+    async_credential = DefaultAzureCredential()
+    token_provider = get_bearer_token_provider(async_credential, "https://cognitiveservices.azure.com/.default")
+    client = OpenAIChatClient(
+        base_url=f"{os.environ['AZURE_OPENAI_ENDPOINT']}/openai/v1/",
+        api_key=token_provider,
+        model_id=os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT"],
     )
 elif API_HOST == "github":
     client = OpenAIChatClient(
         base_url="https://models.github.ai/inference",
         api_key=os.environ["GITHUB_TOKEN"],
-        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4o"),
+        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4.1-mini"),
     )
 elif API_HOST == "ollama":
     client = OpenAIChatClient(
@@ -48,28 +49,34 @@
     )
 else:
     client = OpenAIChatClient(
-        api_key=os.environ.get("OPENAI_API_KEY"), model_id=os.environ.get("OPENAI_MODEL", "gpt-4o")
+        api_key=os.environ.get("OPENAI_API_KEY"), model_id=os.environ.get("OPENAI_MODEL", "gpt-4.1-mini")
     )
 
 
 # --- Main Agent Logic ---
 async def http_mcp_example() -> None:
-    async with (
-        MCPStreamableHTTPTool(name="Expenses MCP Server", url=MCP_SERVER_URL) as mcp_server,
-        ChatAgent(
-            chat_client=client,
-            name="Expenses Agent",
-            instructions=f"You help users to log expenses. Today's date is {datetime.now().strftime('%Y-%m-%d')}.",
-        ) as agent,
-    ):
-        user_query = "yesterday I bought a laptop for $1200 using my visa."
-        result = await agent.run(user_query, tools=mcp_server)
-        print(result)
+    """Run an agent connected to the local expenses MCP server."""
+    try:
+        async with (
+            MCPStreamableHTTPTool(name="Expenses MCP Server", url=MCP_SERVER_URL) as mcp_server,
+            Agent(
+                client=client,
+                name="Expenses Agent",
+                instructions=f"You help users to log expenses. Today's date is {datetime.now().strftime('%Y-%m-%d')}.",
+                tools=[mcp_server],
+            ) as agent,
+        ):
+            user_query = "yesterday I bought a laptop for $1200 using my visa."
+            result = await agent.run(user_query)
+            print(result.text)
 
-        # Keep the worker alive in production
-        while RUNNING_IN_PRODUCTION:
-            await asyncio.sleep(60)
-            logger.info("Worker still running...")
+            # Keep the worker alive in production
+            while RUNNING_IN_PRODUCTION:
+                await asyncio.sleep(60)
+                logger.info("Worker still running...")
+    finally:
+        if async_credential:
+            await async_credential.close()
 
 
 if __name__ == "__main__":
diff --git a/agents/agentframework_learn.py b/agents/agentframework_learn.py
index 7eb3b03..8e9677f 100644
--- a/agents/agentframework_learn.py
+++ b/agents/agentframework_learn.py
@@ -2,10 +2,9 @@
 import logging
 import os
 
-from agent_framework import ChatAgent, MCPStreamableHTTPTool
-from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework import Agent, MCPStreamableHTTPTool
 from agent_framework.openai import OpenAIChatClient
-from azure.identity import DefaultAzureCredential
+from azure.identity.aio import DefaultAzureCredential, get_bearer_token_provider
 from dotenv import load_dotenv
 from rich import print
 from rich.logging import RichHandler
@@ -20,18 +19,20 @@
 
 # Configure chat client based on API_HOST
 API_HOST = os.getenv("API_HOST", "github")
+async_credential = None
 if API_HOST == "azure":
-    client = AzureOpenAIChatClient(
-        credential=DefaultAzureCredential(),
-        deployment_name=os.environ.get("AZURE_OPENAI_CHAT_DEPLOYMENT"),
-        endpoint=os.environ.get("AZURE_OPENAI_ENDPOINT"),
-        api_version=os.environ.get("AZURE_OPENAI_VERSION"),
+    async_credential = DefaultAzureCredential()
+    token_provider = get_bearer_token_provider(async_credential, "https://cognitiveservices.azure.com/.default")
+    client = OpenAIChatClient(
+        base_url=f"{os.environ['AZURE_OPENAI_ENDPOINT']}/openai/v1/",
+        api_key=token_provider,
+        model_id=os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT"],
     )
 elif API_HOST == "github":
     client = OpenAIChatClient(
         base_url="https://models.github.ai/inference",
         api_key=os.environ["GITHUB_TOKEN"],
-        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4o"),
+        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4.1-mini"),
     )
 elif API_HOST == "ollama":
     client = OpenAIChatClient(
@@ -41,26 +42,33 @@
     )
 else:
     client = OpenAIChatClient(
-        api_key=os.environ.get("OPENAI_API_KEY"), model_id=os.environ.get("OPENAI_MODEL", "gpt-4o")
+        api_key=os.environ.get("OPENAI_API_KEY"), model_id=os.environ.get("OPENAI_MODEL", "gpt-4.1-mini")
     )
 
 
-async def http_mcp_example():
+async def http_mcp_example() -> None:
     """
     Creates an agent that can answer questions about Microsoft documentation
     using the Microsoft Learn MCP server.
     """
-    async with (
-        MCPStreamableHTTPTool(name="Microsoft Learn MCP", url="https://learn.microsoft.com/api/mcp") as mcp_server,
-        ChatAgent(
-            chat_client=client,
-            name="DocsAgent",
-            instructions="You help with Microsoft documentation questions.",
-        ) as agent,
-    ):
-        query = "How to create an Azure storage account using az cli?"
-        result = await agent.run(query, tools=mcp_server)
-        print(result)
+
+    try:
+        async with (
+            MCPStreamableHTTPTool(name="Microsoft Learn MCP", url="https://learn.microsoft.com/api/mcp") as mcp_server,
+            Agent(
+                client=client,
+                name="DocsAgent",
+                instructions="You help with Microsoft documentation questions.",
+                tools=[mcp_server],
+            ) as agent,
+        ):
+            query = "How to create an Azure storage account using az cli?"
+            result = await agent.run(query)
+            print(result.text)
+
+    finally:
+        if async_credential:
+            await async_credential.close()
 
 
 if __name__ == "__main__":
diff --git a/agents/agentframework_tavily.py b/agents/agentframework_tavily.py
deleted file mode 100644
index 0c8104e..0000000
--- a/agents/agentframework_tavily.py
+++ /dev/null
@@ -1,69 +0,0 @@
-import asyncio
-import logging
-import os
-
-from agent_framework import ChatAgent, MCPStreamableHTTPTool
-from agent_framework.azure import AzureOpenAIChatClient
-from agent_framework.openai import OpenAIChatClient
-from azure.identity import DefaultAzureCredential
-from dotenv import load_dotenv
-from rich import print
-from rich.logging import RichHandler
-
-# Configure logging
-logging.basicConfig(level=logging.WARNING, format="%(message)s", datefmt="[%X]", handlers=[RichHandler()])
-logger = logging.getLogger("agentframework_tavily")
-logger.setLevel(logging.INFO)
-
-# Load environment variables
-load_dotenv(override=True)
-
-# Configure chat client based on API_HOST
-API_HOST = os.getenv("API_HOST", "github")
-if API_HOST == "azure":
-    client = AzureOpenAIChatClient(
-        credential=DefaultAzureCredential(),
-        deployment_name=os.environ.get("AZURE_OPENAI_CHAT_DEPLOYMENT"),
-        endpoint=os.environ.get("AZURE_OPENAI_ENDPOINT"),
-        api_version=os.environ.get("AZURE_OPENAI_VERSION"),
-    )
-elif API_HOST == "github":
-    client = OpenAIChatClient(
-        base_url="https://models.github.ai/inference",
-        api_key=os.environ["GITHUB_TOKEN"],
-        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4o"),
-    )
-elif API_HOST == "ollama":
-    client = OpenAIChatClient(
-        base_url=os.environ.get("OLLAMA_ENDPOINT", "http://localhost:11434/v1"),
-        api_key="none",
-        model_id=os.environ.get("OLLAMA_MODEL", "llama3.1:latest"),
-    )
-else:
-    client = OpenAIChatClient(
-        api_key=os.environ.get("OPENAI_API_KEY"), model_id=os.environ.get("OPENAI_MODEL", "gpt-4o")
-    )
-
-
-async def http_mcp_example():
-    """
-    Creates an agent that can search the web using the Tavily MCP server.
-    """
-
-    tavily_key = os.environ["TAVILY_API_KEY"]
-    headers = {"Authorization": f"Bearer {tavily_key}"}
-    async with (
-        MCPStreamableHTTPTool(name="Tavily MCP", url="https://mcp.tavily.com/mcp/", headers=headers) as mcp_server,
-        ChatAgent(
-            chat_client=client,
-            name="WebSearchAgent",
-            instructions="You search the web with Tavily and provide concise answers with links.",
-        ) as agent,
-    ):
-        query = "What's new in Python 3.14? Include relevant links."
-        result = await agent.run(query, tools=mcp_server)
-        print(result)
-
-
-if __name__ == "__main__":
-    asyncio.run(http_mcp_example())
diff --git a/agents/langchainv1_tavily.py b/agents/langchainv1_tavily.py
deleted file mode 100644
index e27ea73..0000000
--- a/agents/langchainv1_tavily.py
+++ /dev/null
@@ -1,84 +0,0 @@
-"""LangChain + Tavily MCP Example
-
-Creates a simple research agent that uses the Tavily MCP server
-to search the web and answer questions with relevant links.
-"""
-
-import asyncio
-import logging
-import os
-
-import azure.identity
-from dotenv import load_dotenv
-from langchain.agents import create_agent
-from langchain_core.messages import HumanMessage
-from langchain_mcp_adapters.client import MultiServerMCPClient
-from langchain_openai import ChatOpenAI
-from pydantic import SecretStr
-from rich.logging import RichHandler
-
-# Configure logging
-logging.basicConfig(level=logging.WARNING, format="%(message)s", datefmt="[%X]", handlers=[RichHandler()])
-logger = logging.getLogger("langchainv1_tavily")
-logger.setLevel(logging.INFO)
-
-# Load environment variables
-load_dotenv(override=True)
-
-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 = ChatOpenAI(
-        model=os.environ.get("AZURE_OPENAI_CHAT_DEPLOYMENT"),
-        base_url=os.environ["AZURE_OPENAI_ENDPOINT"] + "/openai/v1/",
-        api_key=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(os.environ.get("OLLAMA_API_KEY", "none")),
-    )
-else:
-    model = ChatOpenAI(model=os.getenv("OPENAI_MODEL", "gpt-4o-mini"))
-
-
-async def run_agent() -> None:
-    """Run a Tavily-backed research agent via MCP tools."""
-    tavily_key = os.environ["TAVILY_API_KEY"]
-    client = MultiServerMCPClient(
-        {
-            "tavily": {
-                "url": "https://mcp.tavily.com/mcp/",
-                "transport": "streamable_http",
-                "headers": {"Authorization": f"Bearer {tavily_key}"},
-            }
-        }
-    )
-
-    # Fetch available tools and create the agent
-    tools = await client.get_tools()
-    agent = create_agent(model, tools, prompt="You search the web and include relevant links in answers.")
-
-    query = "What's new in Python 3.14? Include relevant links."
-    response = await agent.ainvoke({"messages": [HumanMessage(content=query)]})
-
-    final_response = response["messages"][-1].content
-    print(final_response)
-
-
-def main() -> None:
-    asyncio.run(run_agent())
-
-
-if __name__ == "__main__":
-    main()
diff --git a/pyproject.toml b/pyproject.toml
index bd80f84..cf8d49c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -16,7 +16,7 @@ dependencies = [
     "langchain-openai>=1.0.1",
     "langchain-mcp-adapters>=0.1.11",
     "azure-ai-agents>=1.1.0",
-    "agent-framework>=1.0.0b251016",
+    "agent-framework>=1.0.0rc5",
     "azure-cosmos>=4.9.0",
     "azure-monitor-opentelemetry>=1.8.3",
     "opentelemetry-instrumentation-starlette>=0.60b0",
diff --git a/uv.lock b/uv.lock
index 025a2b7..e7b4fff 100644
--- a/uv.lock
+++ b/uv.lock
@@ -17,23 +17,28 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/ba/9b/82df9530ed77d30831c49ffffc827222961422d444c0d684101e945ee214/a2a_sdk-0.3.10-py3-none-any.whl", hash = "sha256:b216ccc5ccfd00dcfa42f0f2dc709bc7ba057550717a34b0b1b34a99a76749cf", size = 140291 },
 ]
 
+[[package]]
+name = "ag-ui-protocol"
+version = "0.1.13"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pydantic" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/04/b5/fc0b65b561d00d88811c8a7d98ee735833f81554be244340950e7b65820c/ag_ui_protocol-0.1.13.tar.gz", hash = "sha256:811d7d7dcce4783dec252918f40b717ebfa559399bf6b071c4ba47c0c1e21bcb", size = 5671 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/cd/9f/b833c1ab1999da35ebad54841ae85d2c2764c931da9a6f52d8541b6901b2/ag_ui_protocol-0.1.13-py3-none-any.whl", hash = "sha256:1393fa894c1e8416efe184168a50689e760d05b32f4646eebb8ff423dddf8e8f", size = 8053 },
+]
+
 [[package]]
 name = "agent-framework"
-version = "1.0.0b251016"
+version = "1.0.0rc5"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "agent-framework-a2a" },
-    { name = "agent-framework-azure-ai" },
-    { name = "agent-framework-copilotstudio" },
-    { name = "agent-framework-core" },
-    { name = "agent-framework-devui" },
-    { name = "agent-framework-mem0" },
-    { name = "agent-framework-purview" },
-    { name = "agent-framework-redis" },
+    { name = "agent-framework-core", extra = ["all"] },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/6a/38/c565d6fb914d0504465543e81fad6351a0192b936613449f4bcad7158a48/agent_framework-1.0.0b251016.tar.gz", hash = "sha256:84fc34d10358b5b74cfbfd62bd6a0109073a4204dc5509cfffd2ad74db1f1eb2", size = 2073274 }
+sdist = { url = "https://files.pythonhosted.org/packages/0a/bf/64bc9231cef4f23a61c6d6a71f2c9bdc81f1e750418ea884d38abd12ce0f/agent_framework-1.0.0rc5.tar.gz", hash = "sha256:d03a5013f13f3d1c3fa2ed7b5b1806816637e1278884633916a63090490fcf8e", size = 4054945 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ed/ac/1da507f4a4ec70dc30345ddfb1e0421b33e91397ce2c15c74105d75204a4/agent_framework-1.0.0b251016-py3-none-any.whl", hash = "sha256:d92d5765dc55f820c9136ba423a56055863b5e4ef464db7eafcf9896f3f81359", size = 5557 },
+    { url = "https://files.pythonhosted.org/packages/f1/88/032e11af66329c5569b6bd9809c88107ed20e3469a0cc4bc2ee648510930/agent_framework-1.0.0rc5-py3-none-any.whl", hash = "sha256:dc11cbc1034b3ce610cb35e8642994b863e8f006b3ee90718b709a30abf383f4", size = 5500 },
 ]
 
 [[package]]
@@ -49,6 +54,34 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/0e/79/aca9da8f2c4628266737cfc7190f17814d55a4f315afd77ca86927e8db02/agent_framework_a2a-1.0.0b251016-py3-none-any.whl", hash = "sha256:7ac984c36903eb898c2abbb0473745c6b657cec2ec2911087f5740f90986c399", size = 6866 },
 ]
 
+[[package]]
+name = "agent-framework-ag-ui"
+version = "1.0.0b260319"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "ag-ui-protocol" },
+    { name = "agent-framework-core" },
+    { name = "fastapi" },
+    { name = "uvicorn", extra = ["standard"] },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/8e/b5/c067ba0839028c285c3d3265f001eafb11d8450ec67811a60cb5b21f942b/agent_framework_ag_ui-1.0.0b260319.tar.gz", hash = "sha256:d44d75dcc762235527980e1e0347891312e140350da614679e79ffa05ebd7f06", size = 167847 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/9a/33/05e90a4fa7ca8581b04bd34b7dcc22b75774a063a8b98362a9c415799599/agent_framework_ag_ui-1.0.0b260319-py3-none-any.whl", hash = "sha256:dba1ba58037e4b997ee4c919086e7077f8a59ea720dba667fc9e99757ad70d7c", size = 90535 },
+]
+
+[[package]]
+name = "agent-framework-anthropic"
+version = "1.0.0b260319"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "agent-framework-core" },
+    { name = "anthropic" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/a1/5b/1454151a0acf590ade8b8e5d6685aa73ac6de1b6b17dce38ba07e6c40f68/agent_framework_anthropic-1.0.0b260319.tar.gz", hash = "sha256:ed88adfe9629a4751593aa4ef1e1a4d3af2cbf3ceac031d2cc00cce974912c29", size = 15696 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/bf/99/edd1f84e738fba41294600ba67d39ba79aba08c8f2ebd309151771451983/agent_framework_anthropic-1.0.0b260319-py3-none-any.whl", hash = "sha256:31f2a531ca4a9ae083e81422db4469545c6c647e76fea7734df252fb8aac10bb", size = 15663 },
+]
+
 [[package]]
 name = "agent-framework-azure-ai"
 version = "1.0.0b251016"
@@ -64,6 +97,70 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/e1/96/e8db5ee8d5a33429a91061e3c6085d0ce9af01fa7984129997967231d5fa/agent_framework_azure_ai-1.0.0b251016-py3-none-any.whl", hash = "sha256:b6b1f004256bfc015c0b7ffdf75a817a1f0caed49300b99215b91c883d87ce03", size = 13907 },
 ]
 
+[[package]]
+name = "agent-framework-azure-ai-search"
+version = "0.0.0a1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/b5/58/b9c706e03b3407be3c70777124136cf428f7879664f9032e606d23024208/agent_framework_azure_ai_search-0.0.0a1.tar.gz", hash = "sha256:ca60fa77a8c3a55eb954c03de4b74ecf890566220854acaad4e07d56f86f43be", size = 1658 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e6/c0/bd014d57a6718272a10955e679a7e08307cabd9557925350ca6e5f94eae9/agent_framework_azure_ai_search-0.0.0a1-py3-none-any.whl", hash = "sha256:b913cb4640a6a2539b1a008462f6dbdca64b14ad9c2bd68a99fa396b5312e876", size = 2373 },
+]
+
+[[package]]
+name = "agent-framework-azurefunctions"
+version = "1.0.0b260319"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "agent-framework-core" },
+    { name = "agent-framework-durabletask" },
+    { name = "azure-functions" },
+    { name = "azure-functions-durable" },
+]
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