How to Use the Dify MCP in CrewAI

Q: How do I pass Dify tools to a CrewAI agent?

You pass the server URL directly into the agent's mcps parameter during initialization. CrewAI connects to the MCP Server and registers tools like chat and uploadfile automatically.

Q: Can I restrict which CrewAI agents have access to Dify?

Yes, you can. By using MCPServerHTTP from crewai.mcp and defining a toolfilter, you can expose specific tools like feedback to only your manager or supervisor agents.

Q: Do these tools work with CrewAI's local memory features?

Yes, they do. The text retrieved via listmessages can be indexed into CrewAI's local vector memory, allowing agents to reference historical facts during subsequent tasks.

Q: How does this setup protect my files and conversation history?

All raw file bytes sent via uploadfile and message logs fetched via listmessages are processed inside secure, isolated V8 instances. This ensures your proprietary documents and chat histories remain strictly private and inaccessible to third parties.

Coordinate cooperative agent teams using CrewAI to execute complex Dify workflows autonomously.

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Connect Dify MCP to CrewAI

Create your Vinkius account to connect Dify 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 with CrewAI

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Coordinate Multi-Agent Teams via CrewAI and Dify

The `chat` tool allows your specialized CrewAI agents to interact with Dify's managed LLM runtimes. In a multi-agent setup, your Researcher agent can gather context, while your Writer agent uses this tool to generate the final response. This splits the cognitive load across multiple specialized roles instead of relying on a single prompt. CrewAI's shared memory system keeps track of the conversation state across these handoffs. Each agent knows what the previous agent accomplished. This ensures the output remains coherent even when multiple models contribute to the final answer.

Extract Chat History for Crew Context

The `list_messages` and `list_conversations` tools inject historic context directly into the CrewAI short-term memory system. Before a crew starts a new task, a coordinator agent runs these tools to read what was previously discussed. This prevents the crew from repeating research or asking duplicate questions. You don't need to manually pass history arrays between Python classes. The MCP Server exposes the history natively, allowing your crew to self-correct based on past interactions. This keeps your autonomous operations running smoothly over long-lived sessions.

Ingest Files for Team Analysis

The `upload_file` tool uploads documents directly to the platform so your entire crew can access the same source files. When a user uploads a PDF, a routing agent triggers this tool to store the document in the shared space. From there, any agent in the crew can query the file content during execution. This eliminates the need to write custom file-parsing scripts for each agent. The platform handles the document processing, while your CrewAI team focuses on analyzing the extracted data. This design keeps your Python codebase lean and focused on agent logic.

Setup guide

Set up Dify 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 tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Dify transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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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 Analyst",
        goal="Access and analyze Dify data via MCP.",
        backstory="Expert analyst with direct Dify access.",
        tools=mcp_tools,
    )

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

You pass the server URL directly into the agent's `mcps` parameter during initialization. CrewAI connects to the MCP Server and registers tools like `chat` and `upload_file` automatically.

Yes, you can. By using `MCPServerHTTP` from `crewai.mcp` and defining a `tool_filter`, you can expose specific tools like `feedback` to only your manager or supervisor agents.

CrewAI schedules tool execution based on the task dependency graph. If multiple agents need to run tools via this MCP Server, the framework executes them sequentially or hierarchically as defined by your crew's process.

Yes, they do. The text retrieved via `list_messages` can be indexed into CrewAI's local vector memory, allowing agents to reference historical facts during subsequent tasks.

All raw file bytes sent via `upload_file` and message logs fetched via `list_messages` are processed inside secure, isolated V8 instances. This ensures your proprietary documents and chat histories remain strictly private and inaccessible to third parties.

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