How to Use the Dify.AI SDK MCP in AutoGen

Q: How do I add Dify.AI SDK tools to an AutoGen assistant?

Install autogen-extmcp and use the mcpservertools helper with your Vinkius endpoint. Pass the resulting tool list directly into your AssistantAgent constructor to give them access to Dify.

Q: How do AutoGen agents handle schema mismatches with the Dify.AI SDK?

The McpToolAdapter automatically converts the 14 Dify tool schemas into the format AutoGen expects. This allows your agents to query getworkflowinfo and execute runs without manual JSON translation.

Q: Is it possible to halt a running Dify generation from AutoGen?

Yes, any agent in your team can invoke stopchatgeneration if it detects an issue. This is useful for budget control or when a supervisor agent decides a response is going off-topic.

Q: How does the AutoGen MCP integration protect conversational logs?

All conversation records retrieved via getconversationmessages are processed in-memory within isolated environments. Vinkius does not log the contents of your Dify chats or workflow payloads, ensuring strict data privacy.

Let AutoGen agents debate, execute, and refine Dify AI workflows through consensus.

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Connect Dify.AI SDK MCP to AutoGen

Create your Vinkius account to connect Dify.AI SDK 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.AI SDK with AutoGen

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Coordinate AutoGen Agents Using Dify Workflows

Let your coordinator agent trigger complex backend processes via `run_workflow`. A second auditor agent can then check the output, while a third uses `submit_feedback` to log performance metrics back to Dify. This MCP Server ensures that workflows aren't run blindly. The agents discuss the execution parameters returned by `get_workflow_parameters` before committing to the run.

Manage Chat Conversations via AutoGen Teams

Assign an agent to manage user sessions using `get_conversations` and `rename_conversation`. This agent keeps track of active threads while other agents focus on generating content via `chat_message`. If a generation goes off track or violates security policies, a moderation agent can trigger `stop_chat_generation` immediately. This provides a safety net during live, multi-agent chat sessions.

Validate Dify Completions with AutoGen Debate

Use `send_completion` to generate raw text, then let your AutoGen agents debate its accuracy. One agent analyzes the text, another suggests improvements, and a third fetches `get_suggested_questions` to expand the topic. If the consensus is negative, the team can programmatically trigger `delete_conversation` to clean up the workspace. This keeps your Dify environment clean and free of junk data.

Setup guide

Set up Dify.AI SDK 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.AI SDK 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.AI SDK_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Dify.AI SDK 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="Dify.AI SDK_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Install `autogen-ext[mcp]` and use the `mcp_server_tools` helper with your Vinkius endpoint. Pass the resulting tool list directly into your `AssistantAgent` constructor to give them access to Dify.

Yes, agents can coordinate by passing conversation IDs retrieved from `get_conversations`. This lets one agent read the history using `get_conversation_messages` while another sends the next `chat_message`.

The `McpToolAdapter` automatically converts the 14 Dify tool schemas into the format AutoGen expects. This allows your agents to query `get_workflow_info` and execute runs without manual JSON translation.

Yes, any agent in your team can invoke `stop_chat_generation` if it detects an issue. This is useful for budget control or when a supervisor agent decides a response is going off-topic.

All conversation records retrieved via `get_conversation_messages` are processed in-memory within isolated environments. Vinkius does not log the contents of your Dify chats or workflow payloads, ensuring strict data privacy.

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