How to Use the Beekeeper MCP in CrewAI

Q: How can a CrewAI agent find a specific user in Beekeeper?

The agent would use the searchusers tool. You can give it a role like 'User Directory Specialist' and task it with finding users by name or email to pass to other agents.

Q: How do I give my CrewAI agents access to these Beekeeper tools?

It's simple. After pip install "crewaitools", you pass your Vinkius MCP server URL directly into the mcps list when defining your Agent. For more control, you can use MCPServerHTTP to filter which tools each agent gets.

Deploy an autonomous CrewAI team to manage your Beekeeper community. Monitor streams, moderate content, and onboard users 24/7.

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Connect Beekeeper MCP to CrewAI

Create your Vinkius account to connect Beekeeper 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 Beekeeper with CrewAI

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Build a Moderation Crew

Assign roles to a team of CrewAI agents to manage your Beekeeper instance. One agent's job is to periodically `list_posts` in high-traffic streams to monitor for keywords. A second agent takes over when a flagged post is found. It can `get_user` to check the poster's profile and then use `send_message` to issue a warning or notify a human moderator. This team works around the clock.

Deploy an Analytics Team with CrewAI

Create a crew for gathering insights from Beekeeper. A 'Researcher' agent can `list_streams` and `list_posts` to collect all activity data for a given period. It then passes this data to an 'Analyst' agent, which processes the information, like counting posts per user or identifying top contributors. Finally, a 'Writer' agent can `create_post` in a private 'reports' stream with a summary. This entire workflow, powered by the MCP server, runs without any manual steps.

Automate User Onboarding and Support

A 'Welcome' agent can monitor for new users by periodically running `list_users`. When a new user appears, it can `send_message` with a welcome note and links to important streams. You can also set up a 'Support' agent. It could monitor a specific stream for help requests. When a request is detected, it could use `search_users` to find an on-call support person and then use `send_message` to alert them with a link to the post.

Setup guide

Set up Beekeeper 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 Beekeeper tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Beekeeper 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 Beekeeper. 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 Beekeeper MCP in CrewAI

The agent would use the `search_users` tool. You can give it a role like 'User Directory Specialist' and task it with finding users by name or email to pass to other agents.

Yes, that's a perfect use case. One agent gathers data with `list_posts`, another summarizes it, and a third uses `create_post` to publish the summary. CrewAI's sequential task execution makes this straightforward.

It's simple. After `pip install "crewai[tools]"`, you pass your Vinkius MCP server URL directly into the `mcps` list when defining your Agent. For more control, you can use `MCPServerHTTP` to filter which tools each agent gets.

That's exactly how CrewAI is designed to work. An agent can run `list_groups`, find the right one, and pass its ID through shared memory to another agent tasked with posting content or managing users for that group.

The server only handles the data for the immediate task, like post content or user lists. All operations run in a dedicated, secure sandbox on Vinkius. Nothing is stored, and each agent's session is completely isolated from others.

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