Give your agent tool access via MCP

Create a per-user MCP server with whitelisted, pre-authenticated tools; then hand your agent a single URL.

When your agent needs to act on behalf of a user (reading their email, creating calendar events), each user must authenticate to each service separately. Managing those credentials in your agent adds complexity and security risk.

Scalekit solves this with per-user MCP servers. You define which tools and connections a server exposes, and Scalekit gives you a unique, pre-authenticated URL for each user. Hand that URL to your agent; it calls tools through MCP, Scalekit handles the auth. MCP servers only support Streamable HTTP transport.

How it works

Two objects are central to this model:

Object	What it is	Created
MCP config	A reusable template that defines which connections and tools are exposed	Once, by your app
MCP instance	A per-user instantiation of a config, with its own URL	Once per user

Your app creates a config once, then calls ensure_instance whenever a new user needs access. Scalekit generates a unique URL for that user. When the agent calls tools through that URL, Scalekit routes each call using the user’s pre-authorized credentials.

Architecture diagram showing how Scalekit MCP works: app creates a config, Scalekit creates per-user instances with unique URLs, users authorize OAuth connections, and the agent connects via MCP URL

Prerequisites

Before you start, make sure you have:

Scalekit API credentials: go to Dashboard → Settings and copy your environment_url, client_id and client_secret
Gmail and Google Calendar connections configured in Scalekit:
- Gmail: Dashboard → AgentKit > Connections > Create Connection → select Gmail → set Connection Name = MY_GMAIL → Save
- Google Calendar: Dashboard → AgentKit > Connections > Create Connection → select Google Calendar → set Connection Name = MY_CALENDAR → Save

Install the SDK and initialize the client

Install the Scalekit Python SDK:

pip install scalekit-sdk-python python-dotenv>=1.0.1

Initialize the client using your environment credentials:

import os
import scalekit.client
from scalekit.actions.models.mcp_config import McpConfigConnectionToolMapping

scalekit_client = scalekit.client.ScalekitClient(
    client_id=os.getenv("SCALEKIT_CLIENT_ID"),
    client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),
    env_url=os.getenv("SCALEKIT_ENV_URL"),
)
my_mcp = scalekit_client.actions.mcp

Create an MCP config

An MCP config is a reusable template. It declares which connections and tools your server exposes. Create it once, not once per user.

cfg_response = my_mcp.create_config(
    name="reminder-manager",
    description="Summarizes latest email and creates a reminder event",
    connection_tool_mappings=[
        McpConfigConnectionToolMapping(
            connection_name="MY_GMAIL",
            tools=["gmail_fetch_mails"],
        ),
        McpConfigConnectionToolMapping(
            connection_name="MY_CALENDAR",
            tools=["googlecalendar_create_event"],
        ),
    ],
)
config_name = cfg_response.config.name

Get a per-user MCP URL
Section titled “Get a per-user MCP URL”

Call ensure_instance to get a unique MCP URL for a specific user. If an instance already exists for that user, Scalekit returns it; it’s safe to call on every login.
```
inst_response = my_mcp.ensure_instance(
    config_name=config_name,
    user_identifier="john-doe",
)
mcp_url = inst_response.instance.url
print("MCP URL:", mcp_url)
```
Before the agent can use this URL, the user must authorize each connection. Retrieve the auth links and surface them to the user:
```
auth_state_response = my_mcp.get_instance_auth_state(
    instance_id=inst_response.instance.id,
    include_auth_links=True,
)
for conn in getattr(auth_state_response, "connections", []):
    print("Connection:", conn.connection_name,
          "| Status:", conn.connected_account_status,
          "| Auth link:", conn.authentication_link)
```
Open the printed links in your browser and complete authentication for each connection.
In production, surface these links to users via your app UI, email, or a Slack message. Poll get_instance_auth_state (without include_auth_links) to check when a user has completed authorization before passing the URL to your agent.

At this point you have a per-user MCP URL. You can pass it to any spec-compliant MCP client: MCP Inspector, Claude Desktop, or an agent framework. The next step shows an example using LangChain.

Connect an agent (LangChain example)

Install the LangChain dependencies:

pip install langgraph>=0.6.5 langchain-mcp-adapters>=0.1.9 openai>=1.53.0

Set your OpenAI API key:

export OPENAI_API_KEY=your-openai-api-key

Pass the MCP URL to a LangChain agent. The agent discovers available tools automatically; no additional auth configuration required:

import asyncio
from langgraph.prebuilt import create_react_agent
from langchain_mcp_adapters.client import MultiServerMCPClient

async def run_agent(mcp_url: str):
    client = MultiServerMCPClient(
        {
            "reminder_demo": {
                "transport": "streamable_http",
                "url": mcp_url,
            },
        }
    )
    tools = await client.get_tools()
    agent = create_react_agent("openai:gpt-4.1", tools)
    response = await agent.ainvoke({
        "messages": "Get my latest email and create a calendar reminder in the next 15 minutes."
    })
    print(response)

asyncio.run(run_agent(mcp_url))

Full working code for all steps above is on GitHub.

Next steps

LangChain integration Use LangChain to build agents that connect to Scalekit MCP servers.

Google ADK integration Connect Scalekit tools to agents built with Google's Agent Development Kit.

Manage connections Learn how to configure and manage connector connections in Scalekit.