How to Use the Framer MCP in LangChain

Q: How do I sync my database to Framer using LangChain?

You build a chain that fetches data and passes it to the createcollectionitem tool. The MCP server handles the API handshake for you.

Build automated content chains in LangChain by connecting your agent directly to your Framer projects and CMS collections.

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Connect Framer MCP to LangChain

Create your Vinkius account to connect Framer to LangChain 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 LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain CMS updates with LangChain

Feed data from external databases directly into your Framer CMS. Your agent uses `create_collection_item` to push new records without manual entry. Chain this with `list_collections` to verify your schema before writing. It turns your site into a dynamic endpoint for your agent pipelines.

Automated site publishing

Trigger deployments programmatically once your content sync completes. Your LangChain agent calls `publish_site` to push changes live instantly. This removes the need for manual clicks in the dashboard. Your workflow stays entirely within the agent's logic flow.

Project discovery for agents

Query your entire Framer account to find specific project IDs. Your agent uses `list_projects` and `get_project` to map out site structures. This context allows the agent to target the correct CMS items. It keeps your automation focused on the right site architecture.

Setup guide

Set up Framer MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Framer tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "framer-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Framer transactions"
    })
    print(result["messages"][-1].content)

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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 LangChain

Yes. By linking these tools, your agent can detect changes in your data and trigger a site update immediately. It replaces manual publishing tasks.

You build a chain that fetches data and passes it to the `create_collection_item` tool. The MCP server handles the API handshake for you.

It does. Each tool is exposed as a callable function. Your agent can iterate through collections or pages as part of its reasoning process.

They stay in your environment variables. The MCP server uses these to authenticate requests without exposing keys to your agent's memory.

We use scoped tokens for access. Only the specific collections you define are reachable by your agent, keeping your site content private.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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