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

Q: How do I integrate Nango (Unified API & Integration Platform) into a CrewAI crew?

Add the server URL to your Agent's mcps list. CrewAI handles the transport and makes the tools available to your agents automatically.

Q: How do I audit Nango syncs using CrewAI?

Create a specialized monitor agent. Task it with checking listsyncs on a schedule to report back any issues to your primary crew.

Deploy autonomous integration crews with CrewAI. Audit connections and sync records without human oversight.

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

Create your Vinkius account to connect Nango (Unified API & Integration Platform) to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Nango (Unified API & Integration Platform) with CrewAI

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Monitor connections with CrewAI agents

Assign a monitor agent to watch your OAuth sessions using `list_connections`. It keeps an eye on connection health so your crew knows when to stop acting. If a connection drops, the agent flags it immediately. It’s proactive maintenance for your automated operations.

Sync data with Nango (Unified API & Integration Platform) in CrewAI

Give your research agents access to `list_records`. They pull the data they need to perform analysis without waiting for a human to dump a CSV. It turns your crew into a self-sufficient unit. They fetch, parse, and act on the data retrieved through the unified API.

Automate Nango (Unified API & Integration Platform) tasks

Use `list_syncs` to let your moderator agent decide if a process should continue. If the sync history shows a success, the next agent in the crew proceeds. It creates a logical chain of execution. Your agents act based on the actual status of your data pipelines.

Setup guide

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

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Nango (Unified API & Integration Platform) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Nango (Unified API & Integration Platform) Analyst",
    goal="Access and analyze Nango (Unified API & Integration Platform) data via MCP.",
    backstory="Expert analyst with direct Nango (Unified API & Integration Platform) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Nango (Unified API & Integration Platform) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

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

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Nango (Unified API & Integration Platform) Analyst",
        goal="Access and analyze Nango (Unified API & Integration Platform) data via MCP.",
        backstory="Expert analyst with direct Nango (Unified API & Integration Platform) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Nango (Unified API & Integration Platform) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 CrewAI

Add the server URL to your Agent's `mcps` list. CrewAI handles the transport and makes the tools available to your agents automatically.

You can share tools across the crew or use a tool filter to restrict access. This ensures only the correct agent manages your integrations.

It works perfectly. The manager agent can trigger the tools, evaluate the results, and then delegate tasks to your worker agents.

Create a specialized monitor agent. Task it with checking `list_syncs` on a schedule to report back any issues to your primary crew.

The server operates under strict zero-trust principles. Only the connection IDs provided by Nango are used, preventing your agents from accessing raw OAuth secrets.

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