How to Use the MonkeyLearn MCP in CrewAI

Q: Does CrewAI support selective tool exposure for MonkeyLearn?

You can use a toolfilter to limit which agents have access to which tools. This keeps your specialized agents focused on their tasks.

Q: Can a CrewAI agent list my MonkeyLearn tag trees?

Yes, the agent can call listtagtrees to understand the taxonomy. This helps the agent make better decisions during the classification phase.

Deploy specialized text analysis crews with the MonkeyLearn MCP Server and CrewAI.

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Connect MonkeyLearn MCP to CrewAI

Create your Vinkius account to connect MonkeyLearn 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 MonkeyLearn with CrewAI

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Specialized classification agents in CrewAI

Assign a dedicated agent to run `classify_text` for incoming data. Other agents in your crew can then act on these classifications to resolve tickets. This keeps your operations orderly. One agent handles the analysis while another performs the action, ensuring clear separation of duties.

Collaborative extraction tasks for CrewAI

Use `extract_text` to feed structured data to your researchers. By sharing memory, your crew can build a comprehensive view of customer intent. Agents handle the heavy lifting of parsing text. They pass the extracted entities to the next agent, creating a smooth pipeline without manual intervention.

Monitor account activity with CrewAI

Have your moderator agent call `list_activity` to track usage. This keeps your crew aware of any issues before they affect your production pipeline. You maintain oversight of the entire system. If the activity logs show errors, the moderator agent can alert your team or throttle the crew's speed.

Setup guide

Set up MonkeyLearn 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 MonkeyLearn tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent MonkeyLearn 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 →

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Common questions about MonkeyLearn MCP in CrewAI

Yes, you can share the toolset among your crew members. Each agent can call `classify_text` or `extract_text` as needed for their specific role.

Pass the server URL in your agent definition using the mcps parameter. This connects your crew to the MonkeyLearn tools immediately.

You can use a tool_filter to limit which agents have access to which tools. This keeps your specialized agents focused on their tasks.

Your text is only sent to the API when an agent explicitly triggers a tool. We keep the transmission locked to the specific payload you provided.

Yes, the agent can call `list_tag_trees` to understand the taxonomy. This helps the agent make better decisions during the classification phase.

Use it with your favorite AI tools

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