How to Use the Archbee MCP in CrewAI

Q: How do I connect my CrewAI agents to the Archbee MCP server?

Pass your server endpoint directly into the agent's mcps array during initialization. This grants your entire crew access to tools like syncopenapi and publishspace immediately.

Q: Can I restrict specific CrewAI agents from deleting Archbee spaces?

Yes, use MCPServerHTTP with a toolfilter to limit tool access. Allow your writer agent to use createupdatedoc while blocking it from calling deletespace.

Deploy specialized agent teams in CrewAI to audit, write, and publish your Archbee documentation autonomously.

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Connect Archbee MCP to CrewAI

Create your Vinkius account to connect Archbee 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 Archbee with CrewAI

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Coordinate documentation audits with CrewAI

The `search_docs` tool scans your entire organization to locate outdated technical guides and broken links. Your CrewAI auditor agent executes this search, while a separate writer agent uses `get_doc` to retrieve and rewrite the flagged files. This multi-agent team divides the labor, allowing one specialist to locate issues while another drafts corrections. You get clean, updated documentation without wasting hours on manual edits.

Automate technical writing with an MCP Server team

The `create_update_doc` tool writes fresh technical content directly into your specified spaces. In a CrewAI setup, a technical writer agent drafts the markdown, and an editor agent uses `import_content` to structure the files correctly. By sharing memory across the team, the agents maintain a consistent tone and structure. They work in parallel, ensuring that new features are documented the moment they are merged.

Manage space hierarchies and lifecycles autonomously

The `clone_space` tool duplicates existing templates to set up standardized developer portals for new API versions. Your operations agent executes this setup, while a coordinator agent organizes them using `create_space_group`. The team cleans up old versions by running `delete_space` once a product reaches end-of-life when managing spaces via this MCP Server. This keeps your documentation portal organized and prevents users from landing on deprecated guides.

Setup guide

Set up Archbee 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 Archbee tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass your server endpoint directly into the agent's `mcps` array during initialization. This grants your entire crew access to tools like `sync_openapi` and `publish_space` immediately.

Yes, use `MCPServerHTTP` with a `tool_filter` to limit tool access. Allow your writer agent to use `create_update_doc` while blocking it from calling `delete_space`.

Agents pass context through shared memory. One agent drafts content using `create_update_doc`, and a moderator agent reviews and executes `merge_suggestion` to finalize the draft.

Yes, agents can run tasks concurrently using this MCP Server. One agent syncs your API schemas using `sync_openapi` while another uploads assets via `upload_file`.

All operations run within your own infrastructure using secure environment variables. Your technical documentation, organization exports from `export_organization`, and workspace structures are never exposed to external networks.

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