> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openhands.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Model Context Protocol

> Model Context Protocol (MCP) enables dynamic tool integration from external servers. Agents can discover and use MCP-provided tools automatically.

export const path_to_script_1 = "examples/01_standalone_sdk/08_mcp_with_oauth.py"

export const path_to_script_0 = "examples/01_standalone_sdk/07_mcp_integration.py"

<Info>
  ***MCP*** (Model Context Protocol) is a protocol for exposing tools and resources to AI agents.
  Read more about MCP [here](https://modelcontextprotocol.io/).
</Info>

## Basic MCP Usage

> The ready-to-run basic MCP usage example is available [here](#ready-to-run-basic-mcp-usage-example)!

<Steps>
  <Step>
    ### MCP Configuration

    Configure MCP servers using a dictionary with server names and connection details following [this configuration format](https://gofastmcp.com/clients/client#configuration-format)

    ```python mcp_config icon="python" wrap focus={3-10} theme={null}
    mcp_config = {
        "mcpServers": {
            "fetch": {
                "command": "uvx",
                "args": ["mcp-server-fetch"]
            },
            "repomix": {
                "command": "npx",
                "args": ["-y", "repomix@1.4.2", "--mcp"]
            },
        }
    }
    ```
  </Step>

  <Step>
    ### Tool Filtering

    Use `filter_tools_regex` to control which MCP tools are available to the agent

    ```python filter_tools_regex focus={4-5} icon="python" theme={null}
    agent = Agent(
        llm=llm,
        tools=tools,
        mcp_config=mcp_config,
        filter_tools_regex="^(?!repomix)(.*)|^repomix.*pack_codebase.*$",
    )
    ```
  </Step>
</Steps>

## MCP with OAuth

> The ready-to-run MCP with OAuth example is available [here](#ready-to-run-mcp-with-oauth-example)!

For MCP servers requiring OAuth authentication:

* Configure OAuth-enabled MCP servers by specifying the URL and auth type
* The SDK automatically handles the OAuth flow when first connecting
* When the agent first attempts to use an OAuth-protected MCP server's tools, the SDK initiates the OAuth flow via [FastMCP](https://gofastmcp.com/servers/auth/authentication)
* User will be prompted to authenticate via browser
* Access tokens are securely stored in `~/.fastmcp/oauth-mcp-client-cache/` and automatically refreshed by FastMCP as needed

```python mcp_config focus={5} icon="python" wrap theme={null}
mcp_config = {
    "mcpServers": {
        "Notion": {
            "url": "https://mcp.notion.com/mcp",
            "auth": "oauth"
        }
    }
}
```

<Note>
  OAuth MCP servers require user interaction for the initial browser-based authentication. This means they are not suitable for fully automated/headless workflows. If you need headless access, check if the MCP provider offers API key authentication as an alternative.
</Note>

## Ready-to-Run Basic MCP Usage Example

<Note>
  This example is available on GitHub: [examples/01\_standalone\_sdk/07\_mcp\_integration.py](https://github.com/OpenHands/software-agent-sdk/blob/main/examples/01_standalone_sdk/07_mcp_integration.py)
</Note>

Here's an example integrating MCP servers with an agent:

```python icon="python" expandable examples/01_standalone_sdk/07_mcp_integration.py theme={null}
import os

from pydantic import SecretStr

from openhands.sdk import (
    LLM,
    Agent,
    Conversation,
    Event,
    LLMConvertibleEvent,
    get_logger,
)
from openhands.sdk.security.llm_analyzer import LLMSecurityAnalyzer
from openhands.sdk.tool import Tool
from openhands.tools.file_editor import FileEditorTool
from openhands.tools.terminal import TerminalTool


logger = get_logger(__name__)

# Configure LLM
api_key = os.getenv("LLM_API_KEY")
assert api_key is not None, "LLM_API_KEY environment variable is not set."
model = os.getenv("LLM_MODEL", "anthropic/claude-sonnet-4-5-20250929")
base_url = os.getenv("LLM_BASE_URL")
llm = LLM(
    usage_id="agent",
    model=model,
    base_url=base_url,
    api_key=SecretStr(api_key),
)

cwd = os.getcwd()
tools = [
    Tool(name=TerminalTool.name),
    Tool(name=FileEditorTool.name),
]

# Add MCP Tools
mcp_config = {
    "mcpServers": {
        "fetch": {"command": "uvx", "args": ["mcp-server-fetch"]},
        "repomix": {"command": "npx", "args": ["-y", "repomix@1.4.2", "--mcp"]},
    }
}
# Agent
agent = Agent(
    llm=llm,
    tools=tools,
    mcp_config=mcp_config,
    # This regex filters out all repomix tools except pack_codebase
    filter_tools_regex="^(?!repomix)(.*)|^repomix.*pack_codebase.*$",
)

llm_messages = []  # collect raw LLM messages


def conversation_callback(event: Event):
    if isinstance(event, LLMConvertibleEvent):
        llm_messages.append(event.to_llm_message())


# Conversation
conversation = Conversation(
    agent=agent,
    callbacks=[conversation_callback],
    workspace=cwd,
)
conversation.set_security_analyzer(LLMSecurityAnalyzer())

logger.info("Starting conversation with MCP integration...")
conversation.send_message(
    "Read https://github.com/OpenHands/OpenHands and write 3 facts "
    "about the project into FACTS.txt."
)
conversation.run()

conversation.send_message("Great! Now delete that file.")
conversation.run()

print("=" * 100)
print("Conversation finished. Got the following LLM messages:")
for i, message in enumerate(llm_messages):
    print(f"Message {i}: {str(message)[:200]}")

# Report cost
cost = llm.metrics.accumulated_cost
print(f"EXAMPLE_COST: {cost}")
```

You can run the example code as-is.

<Note>
  The model name should follow the [LiteLLM convention](https://models.litellm.ai/): `provider/model_name` (e.g., `anthropic/claude-sonnet-4-5-20250929`, `openai/gpt-4o`).
  The `LLM_API_KEY` should be the API key for your chosen provider.
</Note>

<CodeGroup>
  <CodeBlock language="bash" filename="Bring-your-own provider key" icon="terminal" wrap>
    {`export LLM_API_KEY="your-api-key"\nexport LLM_MODEL="anthropic/claude-sonnet-4-5-20250929"  # or openai/gpt-4o, etc.\ncd software-agent-sdk\nuv run python ${path_to_script_0}`}
  </CodeBlock>

  <CodeBlock language="bash" filename="OpenHands Cloud" icon="terminal" wrap>
    {`# https://app.all-hands.dev/settings/api-keys\nexport LLM_API_KEY="your-openhands-api-key"\nexport LLM_MODEL="openhands/claude-sonnet-4-5-20250929"\ncd software-agent-sdk\nuv run python ${path_to_script_0}`}
  </CodeBlock>
</CodeGroup>

<Tip>
  **ChatGPT Plus/Pro subscribers**: You can use `LLM.subscription_login()` to authenticate with your ChatGPT account and access Codex models without consuming API credits. See the [LLM Subscriptions guide](/sdk/guides/llm-subscriptions) for details.
</Tip>

## Ready-to-Run MCP with OAuth Example

<Note>
  This example is available on GitHub: [examples/01\_standalone\_sdk/08\_mcp\_with\_oauth.py](https://github.com/OpenHands/software-agent-sdk/blob/main/examples/01_standalone_sdk/08_mcp_with_oauth.py)
</Note>

```python icon="python" expandable examples/01_standalone_sdk/08_mcp_with_oauth.py theme={null}
import os

from pydantic import SecretStr

from openhands.sdk import (
    LLM,
    Agent,
    Conversation,
    Event,
    LLMConvertibleEvent,
    get_logger,
)
from openhands.sdk.tool import Tool
from openhands.tools.file_editor import FileEditorTool
from openhands.tools.terminal import TerminalTool


logger = get_logger(__name__)

# Configure LLM
api_key = os.getenv("LLM_API_KEY")
assert api_key is not None, "LLM_API_KEY environment variable is not set."
model = os.getenv("LLM_MODEL", "anthropic/claude-sonnet-4-5-20250929")
base_url = os.getenv("LLM_BASE_URL")
llm = LLM(
    usage_id="agent",
    model=model,
    base_url=base_url,
    api_key=SecretStr(api_key),
)

cwd = os.getcwd()
tools = [
    Tool(
        name=TerminalTool.name,
    ),
    Tool(name=FileEditorTool.name),
]

mcp_config = {
    "mcpServers": {"Notion": {"url": "https://mcp.notion.com/mcp", "auth": "oauth"}}
}
agent = Agent(llm=llm, tools=tools, mcp_config=mcp_config)

llm_messages = []  # collect raw LLM messages


def conversation_callback(event: Event):
    if isinstance(event, LLMConvertibleEvent):
        llm_messages.append(event.to_llm_message())


# Conversation
conversation = Conversation(
    agent=agent,
    callbacks=[conversation_callback],
)

logger.info("Starting conversation with MCP integration...")
conversation.send_message("Can you search about OpenHands V1 in my notion workspace?")
conversation.run()

print("=" * 100)
print("Conversation finished. Got the following LLM messages:")
for i, message in enumerate(llm_messages):
    print(f"Message {i}: {str(message)[:200]}")
```

You can run the example code as-is.

<Note>
  The model name should follow the [LiteLLM convention](https://models.litellm.ai/): `provider/model_name` (e.g., `anthropic/claude-sonnet-4-5-20250929`, `openai/gpt-4o`).
  The `LLM_API_KEY` should be the API key for your chosen provider.
</Note>

<CodeGroup>
  <CodeBlock language="bash" filename="Bring-your-own provider key" icon="terminal" wrap>
    {`export LLM_API_KEY="your-api-key"\nexport LLM_MODEL="anthropic/claude-sonnet-4-5-20250929"  # or openai/gpt-4o, etc.\ncd software-agent-sdk\nuv run python ${path_to_script_1}`}
  </CodeBlock>

  <CodeBlock language="bash" filename="OpenHands Cloud" icon="terminal" wrap>
    {`# https://app.all-hands.dev/settings/api-keys\nexport LLM_API_KEY="your-openhands-api-key"\nexport LLM_MODEL="openhands/claude-sonnet-4-5-20250929"\ncd software-agent-sdk\nuv run python ${path_to_script_1}`}
  </CodeBlock>
</CodeGroup>

<Tip>
  **ChatGPT Plus/Pro subscribers**: You can use `LLM.subscription_login()` to authenticate with your ChatGPT account and access Codex models without consuming API credits. See the [LLM Subscriptions guide](/sdk/guides/llm-subscriptions) for details.
</Tip>

## Next Steps

* **[Custom Tools](/sdk/guides/custom-tools)** - Creating native SDK tools
* **[Security Analyzer](/sdk/guides/security)** - Securing tool usage
* **[MCP Package Source Code](https://github.com/OpenHands/software-agent-sdk/tree/main/openhands-sdk/openhands/sdk/mcp)** - MCP integration implementation