How to Use the Framer MCP in CrewAI

Q: Can CrewAI agents collaborate to update a Framer CMS collection?

Yes, one agent can use listcollections to identify the target structure, while a second agent formats the data and calls createcollectionitem to insert the new items.

Deploy specialized CrewAI agent teams to manage your Framer CMS, audit layouts, and coordinate web publishing.

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Connect Framer MCP to CrewAI

Create your Vinkius account to connect Framer 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 Framer with CrewAI

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Coordinate multi-agent Framer updates with CrewAI

Stop asking a single agent to do everything. With this MCP Server, you can assign a researcher agent to gather data and a publisher agent to run `create_collection_item` and `publish_site` in a structured sequence. CrewAI manages the shared memory and context between these specialized agents. The writer agent drafts the content, while the manager agent verifies the structure before committing it to your web project.

Autonomous site auditing and page mapping

Let your agent crews run continuous checks on your web layouts. One agent can list all active pages with `list_pages` while another checks the site configuration using `get_site_info`. They compare the actual live structure against your internal sitemaps. If they find missing pages or incorrect settings, they flag the discrepancy or automatically fix the layouts.

Hierarchical content publishing pipelines

Establish clear chains of command for your web deployments. A moderator agent can review the work of a writer agent, calling `list_collection_items` to ensure no duplicate content exists before publishing. Once the moderator approves, the specialized publishing agent takes over to run `publish_site`. This structured workflow keeps your live production site clean and error-free.

Setup guide

Set up Framer 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 Framer tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the Vinkius MCP URL directly into the agent's mcps parameter during initialization. You can restrict tools so only your publisher agent has access to publish_site.

Yes, one agent can use list_collections to identify the target structure, while a second agent formats the data and calls create_collection_item to insert the new items.

The framework manages agent execution speed, but you can also configure rate limit handlers. If an agent hits a limit while running list_collection_items, it will back off and retry once the window resets.

No, you don't. CrewAI natively supports the HTTP and SSE transports used by Vinkius, meaning your agents can connect to the server and fetch get_project data out of the box.

Your Framer project data, API keys, and CMS items are handled through an ephemeral MCP sandbox managed by Vinkius. No credentials or raw payloads are cached on external servers, keeping your web projects secure.

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