How to Use the Nango (Unified API & Integration Platform) MCP in AutoGen

Q: Can an AutoGen agent troubleshoot a sync failure in Nango (Unified API & Integration Platform)?

Yes, an agent can check sync histories using listsyncs and analyze the parameters via getintegration. The agents can then debate the root cause of the sync failure in their chat.

Q: How does the server prevent agents from exposing sensitive integration keys?

The MCP Server only exposes metadata through tools like getenvironment and listintegrations. Raw API secrets and OAuth keys are never returned in the tool outputs, preventing agents from leaking them in conversation logs.

Let AutoGen agents debate integration health and coordinate background syncs using the Nango MCP Server.

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Connect Nango (Unified API & Integration Platform) MCP to AutoGen

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Setup Nango (Unified API & Integration Platform) with AutoGen

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Let AutoGen Agents Audit Live OAuth Connections

Set up a multi-agent conversation where a security agent and a developer agent audit your integrations. The developer agent uses `list_connections` to find active sessions, while the security agent calls `get_connection` to check for compliance risks. If the security agent flags an old connection, they negotiate a resolution. This multi-perspective review ensures your third-party integrations stay secure without requiring constant manual audits.

Resolve Sync Issues via Agent Collaboration

When a background data sync fails, your AutoGen agents can work together to diagnose the issue. One agent calls `list_syncs` to locate the failure, while another pulls the integration parameters using `get_integration`. They compare the configuration against the active environment settings retrieved via `get_environment`. By collaborating, the agents can pinpoint whether the error is due to a misconfigured webhook or an expired token.

Process Unified Records with Dedicated Agents

Divide and conquer large datasets by assigning specific records to specialized agents. A coordinator agent calls `list_records` to retrieve standardized data from Nango and passes individual records to worker agents. This structure lets you process massive batches of external data in parallel. Each agent handles its assigned records, cleans them up, and prepares them for your production database.

Setup guide

Set up Nango (Unified API & Integration Platform) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Nango (Unified API & Integration Platform) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Nango (Unified API & Integration Platform)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Nango (Unified API & Integration Platform) data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Nango (Unified API & Integration Platform)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Nango (Unified API & Integration Platform) data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Nango. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Nango (Unified API & Integration Platform) MCP in AutoGen

You register the tools with your AssistantAgent using the mcp_server_tools helper. This exposes tools like `list_connections` and `list_records` directly to the agents' conversation space using the AutoGen MCP integration.

Yes, an agent can check sync histories using `list_syncs` and analyze the parameters via `get_integration`. The agents can then debate the root cause of the sync failure in their chat.

The McpToolAdapter handles the conversion automatically. It maps Nango's tools, such as `get_environment`, into the schema format that AutoGen's conversational agents expect.

Yes, AutoGen supports stdio transport, allowing your agents to interact with the server directly from your local command line or terminal environment.

The MCP Server only exposes metadata through tools like `get_environment` and `list_integrations`. Raw API secrets and OAuth keys are never returned in the tool outputs, preventing agents from leaking them in conversation logs.

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