Using Pipedream MCP servers with authentication
Call an authenticated Pipedream MCP server over streamable HTTP, passing a bearer token plus project and environment headers on behalf of an end user.
"""
Using Pipedream MCP servers with authentication
This is an example of how to use Pipedream MCP servers with authentication.
This is useful if your app is interfacing with the MCP servers in behalf of your users.
1. Get your access token. You can check how in Pipedream's docs: https://pipedream.com/docs/connect/mcp/developers/
2. Get the URL of the MCP server. It will look like this: https://remote.mcp.pipedream.net/<External user id>/<MCP app slug>
3. Set the environment variables:
- MCP_SERVER_URL: The URL of the MCP server you previously got
- MCP_ACCESS_TOKEN: The access token you previously got
- PIPEDREAM_PROJECT_ID: The project id of the Pipedream project you want to use
- PIPEDREAM_ENVIRONMENT: The environment of the Pipedream project you want to use
3. Install dependencies: uv pip install agno mcp
"""
import asyncio
from os import getenv
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.mcp import MCPTools, StreamableHTTPClientParams
from agno.utils.log import log_exception
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
mcp_server_url = getenv("MCP_SERVER_URL")
mcp_access_token = getenv("MCP_ACCESS_TOKEN")
pipedream_project_id = getenv("PIPEDREAM_PROJECT_ID")
pipedream_environment = getenv("PIPEDREAM_ENVIRONMENT")
server_params = StreamableHTTPClientParams(
url=mcp_server_url,
headers={
"Authorization": f"Bearer {mcp_access_token}",
"x-pd-project-id": pipedream_project_id,
"x-pd-environment": pipedream_environment,
},
)
async def run_agent(task: str) -> None:
try:
async with MCPTools(
server_params=server_params, transport="streamable-http", timeout_seconds=20
) as mcp:
agent = Agent(
model=OpenAIChat(id="gpt-5.2"),
tools=[mcp],
markdown=True,
)
await agent.aprint_response(input=task, stream=True)
except Exception as e:
log_exception(f"Unexpected error: {e}")
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
# The agent can read channels, users, messages, etc.
asyncio.run(run_agent("Show me the latest message in the channel #general"))Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U "agno[mcp]" openaiConnect the end user
Use a Pipedream developer access token obtained with client-credentials OAuth as MCP_ACCESS_TOKEN. Replace the external-user placeholder in the URL with your application's user ID, URL-encoded. This URL supplies the user and Slack app; the code supplies project and environment headers. Use development or production for the environment.
The same external user must connect their Slack account. If no account is connected, follow the connection URL returned by Pipedream. The old URL shape in the preserved source docstring is superseded by this v3 setup.
Export environment variables
export MCP_ACCESS_TOKEN="your_mcp_access_token_here"
export MCP_SERVER_URL="https://remote.mcp.pipedream.net/v3?externalUserId=YOUR_URL_ENCODED_USER_ID&app=slack"
export OPENAI_API_KEY="your_openai_api_key_here"
export PIPEDREAM_ENVIRONMENT="development"
export PIPEDREAM_PROJECT_ID="your_pipedream_project_id_here"Run the example
Save the code above as pipedream_auth.py, then run:
python pipedream_auth.pyFull source: cookbook/91_tools/mcp/pipedream_auth.py