How to Use the Dify.AI SDK MCP in CrewAI

Q: Are Dify.AI SDK workflows compatible with CrewAI?

Yes. Your agents can call runworkflow to execute tasks and share the results across the crew memory.

Q: Can I filter Dify.AI SDK tools in CrewAI?

You can use the toolfilter option in the MCPServerHTTP class. This restricts which agents have access to sensitive tools like deleteconversation.

Deploy specialized agent crews with Dify.AI SDK. Coordinate research and analysis tasks in one unified MCP server setup.

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Connect Dify.AI SDK MCP to CrewAI

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

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Perplexity

Role-based agent collaboration

Assign agents specific tasks using `run_workflow`. One agent can fetch data while another processes the output using `send_completion`. Use `get_workflow_info` to define agent roles based on the available app metadata. This keeps your crew focused on their assigned domain.

Automated session monitoring

Monitor active crews by querying `get_conversations`. Use `get_conversation_messages` to review what your agents said during a multi-step task. If an agent goes off-track, use `delete_conversation` to reset the session. It lets you prune bad data before it impacts the rest of the crew.

Multimodal agent intelligence

Enable agents to read documents by calling `upload_file`. This allows your research agents to analyze external files as part of their collaborative process. Use `get_suggested_questions` to generate follow-up tasks for other agents. It keeps the crew moving through the workflow without manual intervention.

Setup guide

Set up Dify.AI SDK 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 Dify.AI SDK tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Dify.AI SDK Analyst",
    goal="Access and analyze Dify.AI SDK data via MCP.",
    backstory="Expert analyst with direct Dify.AI SDK access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Dify.AI SDK 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="Dify.AI SDK Analyst",
        goal="Access and analyze Dify.AI SDK data via MCP.",
        backstory="Expert analyst with direct Dify.AI SDK access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Dify.AI SDK 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 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 CrewAI

You pass the server URL to the agent's mcps parameter. CrewAI automatically maps the 14 tools for your agents to use.

Yes. Your agents can call `run_workflow` to execute tasks and share the results across the crew memory.

You can use the tool_filter option in the MCPServerHTTP class. This restricts which agents have access to sensitive tools like `delete_conversation`.

It does. You can define a sequence where one agent performs a `chat_message` and the next agent handles the response.

The server manages your conversation logs and metadata in a private environment. Every request requires an endpoint token to keep your data siloed.

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