How to Use the Dify MCP in AutoGen

Q: How do I register Dify tools with my AutoGen conversational agents?

Install autogen-extmcp and use mcpservertools with your server URL. Pass the resulting tool list directly into your AssistantAgent constructor.

Q: How does AutoGen handle schema conversion for Dify tools?

The McpToolAdapter automatically translates the MCP tool definitions into the format AutoGen expects. You do not need to write custom JSON schemas for uploadfile or feedback.

Build consensus-driven AutoGen agent groups that coordinate Dify tasks and analyze chat histories.

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Connect Dify MCP to AutoGen

Create your Vinkius account to connect Dify to AutoGen 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 Dify with AutoGen

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Enable multi-agent debate over Dify operations

Let your AutoGen agents negotiate before executing critical tasks. One agent can draft a message using `chat`, while a supervisor agent reviews the output before submitting it to the channel. This collaborative structure prevents errors in automated workflows. Your agents discuss the system configurations retrieved by `get_parameters` to ensure the correct prompt version is active.

Manage complex conversation audits using this MCP Server

Let a dedicated auditor agent monitor system performance. The agent queries `list_conversations` and evaluates the quality of user interactions without human intervention. If it detects a low rating, the agent submits corrective data using `feedback`. This automated loop keeps your production workflows aligned without manual oversight.

Coordinate file processing across specialized agents

Divide and conquer your document workflows. One ingestion agent handles `upload_file`, a second agent reads the metadata, and a third agent triggers a `chat` session to process the contents. AutoGen's conversational routing handles the handoffs naturally. The output of `list_messages` is passed between agents as plain text, keeping the entire pipeline transparent.

Setup guide

Set up Dify 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 Dify 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="Dify_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Dify data")
print(result.messages[-1].content)

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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="Dify_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Dify 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 Dify. 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 Dify MCP in AutoGen

Install `autogen-ext[mcp]` and use `mcp_server_tools` with your server URL. Pass the resulting tool list directly into your `AssistantAgent` constructor.

Yes. The server supports concurrent requests, meaning your performance agent can call `get_parameters` while your writer agent is actively running a `chat` loop.

The `McpToolAdapter` automatically translates the MCP tool definitions into the format AutoGen expects. You do not need to write custom JSON schemas for `upload_file` or `feedback`.

It does. You can configure your connection using either stdio or Streamable HTTP transports depending on whether you are running a local or cloud-hosted AutoGen setup.

All file payloads and chat messages are sent directly to your Dify instance. Vinkius operates a zero-trust sandbox that handles authentication tokens securely without caching your private data.

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