Builder.io (Visual CMS) MCP Server for LlamaIndexGive LlamaIndex instant access to 9 tools to Admin Graphql, Create Content, Delete Asset By Url, and more

Name: Builder.io (Visual CMS)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Builder.io (Visual CMS) as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Ask AI about this MCP Server for LlamaIndex

Open in ChatGPT Open in Claude Open in Perplexity

The Builder.io (Visual CMS) MCP Server for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 9 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Builder.io (Visual CMS). "
            "You have 9 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Builder.io (Visual CMS)?"
    )
    print(response)

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 Builder.io (Visual CMS) MCP Server

Connect your Builder.io space to any AI agent and take full control of your visual CMS and headless content through natural conversation.

LlamaIndex agents combine Builder.io (Visual CMS) tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Content Management — Fetch entries from any model using get_content or retrieve pre-rendered HTML for components with get_html.
Write Operations — Create, update, or delete content entries programmatically using the Write API tools like create_content and update_content.
Advanced Querying — Execute complex GraphQL queries against the Content API or perform administrative tasks using admin_graphql.
Asset Handling — Upload new media assets or remove existing ones by URL to maintain your digital asset library.
Targeting & Personalization — Use user attributes and MongoDB-style queries to fetch specific content variants.

The Builder.io (Visual CMS) MCP Server exposes 9 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 9 Builder.io (Visual CMS) tools available for LlamaIndex

When LlamaIndex connects to Builder.io (Visual CMS) through Vinkius, your AI agent gets direct access to every tool listed below — spanning visual-cms, graphql, content-api, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

admin

Admin graphql on Builder.io (Visual CMS)

Requires Private API Key. Execute an Admin API GraphQL query/mutation

create

Create content on Builder.io (Visual CMS)

Requires Private API Key. Create a new content entry

delete

Delete asset by url on Builder.io (Visual CMS)

Delete an asset by its URL

delete

Delete content on Builder.io (Visual CMS)

Requires Private API Key. Delete a content entry

get

Get content on Builder.io (Visual CMS)

Get content from a Builder.io model

get

Get html on Builder.io (Visual CMS)

Get pre-rendered HTML for a Builder.io model

query

Query graphql on Builder.io (Visual CMS)

Query Builder.io content using GraphQL

update

Update content on Builder.io (Visual CMS)

Requires Private API Key. Update an existing content entry

upload

Upload asset on Builder.io (Visual CMS)

Requires Private API Key. Upload an asset (image, video, document)

Connect Builder.io (Visual CMS) to LlamaIndex via MCP

Follow these steps to wire Builder.io (Visual CMS) into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 9 tools from Builder.io (Visual CMS)

Why Use LlamaIndex with the Builder.io (Visual CMS) MCP Server

LlamaIndex provides unique advantages when paired with Builder.io (Visual CMS) through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Builder.io (Visual CMS) tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Builder.io (Visual CMS) tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Builder.io (Visual CMS), a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Builder.io (Visual CMS) tools were called, what data was returned, and how it influenced the final answer

Builder.io (Visual CMS) + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Builder.io (Visual CMS) MCP Server delivers measurable value.

Hybrid search: combine Builder.io (Visual CMS) real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Builder.io (Visual CMS) to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Builder.io (Visual CMS) for fresh data

Analytical workflows: chain Builder.io (Visual CMS) queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Builder.io (Visual CMS) in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Builder.io (Visual CMS) immediately.

"Fetch the latest 5 entries from the 'page' model in Builder.io."

"Update the 'announcement-bar' entry with ID 'entry-888' to change the text to 'Sale ends tonight!'."

"Upload this image URL to my Builder assets: https://example.com/hero.jpg"

Troubleshooting Builder.io (Visual CMS) MCP Server with LlamaIndex

Common issues when connecting Builder.io (Visual CMS) to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Builder.io (Visual CMS) + LlamaIndex FAQ

Common questions about integrating Builder.io (Visual CMS) MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Builder.io (Visual CMS) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

Explore More MCP Servers

View all →

Chorus.ai (ZoomInfo)

8 tools

Analyze sales conversations and meetings via Chorus.ai — track transcripts, identify key moments, and monitor team performance directly from any AI agent.