How do I get my Framer API key?

Open your Framer project in the editor. Go to **Site Settings** (gear icon in the top bar), then navigate to the **General** tab. Scroll down to find the **Server API** section and click **Generate API key**. Copy the key and store it securely — treat it like a password. This key is specific to this project. Paste it into the configuration field below.

Can I push content from a spreadsheet into my Framer CMS?

Yes. Your AI agent can create and update CMS collection items programmatically. Describe the data you want to add, and it maps your fields to the Framer collection schema and creates the items — perfect for bulk content migrations or data-driven landing pages.

Does publishing through the API affect my Framer design?

No. The Server API only manages CMS content — it cannot modify your visual design, canvas layout, or component structure. Your designers remain in full control of the visual experience while content teams operate independently through the AI agent.

Is this suitable for agencies managing multiple Framer projects?

Yes. Each API key is bound to a specific Framer project. Configure separate integrations for each client project and your AI agent can switch between them — managing content across your entire portfolio without opening multiple browser tabs.

Framer MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Framer
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Framer through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "framer": {
            "transport": "streamable_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,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Framer, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Framer MCP Server

Connect Framer to your AI agent and manage your website CMS content and publishing workflow conversationally.

LangChain's ecosystem of 500+ components combines seamlessly with Framer through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

CMS Collections — List, create, update, and manage CMS collection items directly from natural language commands.
Content Sync — Push content updates from external data sources into your Framer CMS collections programmatically.
Site Publishing — Trigger site publishes to push your latest CMS changes live.
Collection Schema — Query collection structures and field definitions to understand your content model.

The Framer MCP Server exposes 8 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Framer to LangChain via MCP

Follow these steps to integrate the Framer MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 8 tools from Framer via MCP

Why Use LangChain with the Framer MCP Server

LangChain provides unique advantages when paired with Framer through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Framer MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Framer queries for multi-turn workflows

Framer + LangChain Use Cases

Practical scenarios where LangChain combined with the Framer MCP Server delivers measurable value.

RAG with live data: combine Framer tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Framer, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Framer tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Framer tool call, measure latency, and optimize your agent's performance

Framer MCP Tools for LangChain (8)

These 8 tools become available when you connect Framer to LangChain via MCP:

create_collection_item

Create a new CMS item

get_project

Get project details

get_site_info

Get site configuration

list_collection_items

List items in a CMS collection

list_collections

List CMS collections

list_pages

List all site pages

list_projects

List all Framer projects

publish_site

This makes changes visible to visitors. Publish the website

Example Prompts for Framer in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Framer immediately.

"List all CMS collections in my Framer site."

"Add a new team member 'Ana Silva' to the Team Members collection."

"Publish my Framer site with the latest CMS changes."

Troubleshooting Framer MCP Server with LangChain

Common issues when connecting Framer to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Framer + LangChain FAQ

Common questions about integrating Framer MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.