How do I connect LlamaCloud to my AI agent?

You subscribe to the MCP on Vinkius and enter your LlamaCloud API Key. Once connected, you can use it immediately in any MCP-compatible client.

Can I parse complex PDFs with this MCP?

Yes. You can use the create_parsing_upload capability to send PDFs to LlamaParse, which converts tables and complex layouts into Markdown.

What clients are compatible with this MCP?

This MCP works with any compatible client, including Claude, Cursor, Windsurf, and VS Code.

How do I check if a parsing job is finished?

You can use the list_parsing_jobs capability to see active jobs or use get_parsing_result to pull the final data once it is complete.

Do I need to write code to manage my pipelines?

No. You can list pipelines, get configurations, and manage projects using natural language commands through your AI agent.

Can LlamaParse handle complex tables and layouts in my PDFs?

Absolutely. LlamaParse uses AI-driven parsing to turn complex PDF layouts, nested tables, and even handwriting into structured Markdown. Use the create_parsing_upload capability to start the process and retrieve high-quality context for your agent.

How do I check if my RAG data pipeline is finished processing?

Use the get_parsing_result capability with your specific Job ID. Your agent will poll the LlamaCloud API and report the current status. Once finished, it will retrieve the final parsed content ready for grounding.

Can I see all data sources connected to a specific pipeline?

Yes. The get_pipeline capability extracts the full configuration for any pipeline ID, identifying all connected data sources and configured index settings, ensuring you have a complete view of your ingestion flow.

An astronaut overseeing a futuristic data hub

Download PDF Markdown Version

Connect Llamacloud Managed RAG Parsing to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Run document parsing and data pipelines through your AI agent.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 6 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through LlamaCloud.

01
List pipelines
This capability returns a list of all deployed data pipelines in your LlamaCloud account.
02
Get pipeline
Use this to retrieve the specific configuration settings for a single data pipeline.
03
List projects
Use this to see all active LlamaCloud projects currently in your account.

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through LlamaCloud.

04
List parsing jobs
This capability lists all active LlamaParse jobs so you can track document ingestion progress.
05
Create parsing upload
This capability sends a specific file directly to LlamaParse for processing.
06
Get parsing result
This capability pulls the final Markdown or rich-text extraction once a LlamaParse job finishes.

Real work

What teams actually run

Automated Document Ingestion

An engineer sends a batch of PDFs to LlamaParse and monitors the job status via the agent.

RAG Pipeline Auditing

A developer checks the configuration of a specific pipeline to verify its data sources.

Data Integrity Checks

A data scientist retrieves parsed outputs to ensure tables and handwriting were captured correctly.

Real-time Job Tracking

A user monitors the progress of ongoing parsing jobs to ensure data is ready for indexing.

Automate a task

Put LlamaCloud to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

LlamaCloud works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put LlamaCloud to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

819ms average. Fast in production.

LlamaCloud is checked daily against the live service.

Daily averagePeak 962ms

Oct 3Today

Fastest day: 693ms
Slowest day: 962ms
14-day trend: Slowing+9%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of LlamaCloud, so you can see the experience inside your AI.

It does not authenticate your account with LlamaCloud. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

LlamaCloud Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_AxNi4f2yJsdElAAsexdJyB2PpLLyipZfGMbLBQVd/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — LlamaCloud capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "llamacloud-managed-rag-parsing-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_AxNi4f2yJsdElAAsexdJyB2PpLLyipZfGMbLBQVd/mcp"
    }
  }
}

Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up LlamaCloud in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work LlamaCloud owners hand off.

This MCP is built for technical teams managing large scale RAG implementations.

01
RAG Developers
They use the agent to automate document ingestion and monitor pipeline health.
02
AI Engineers
They use the capabilities to verify parsing quality and run extraction jobs without writing scripts.
03
Data Scientists
They use the agent to audit managed indices and track parsing status for better grounding.

FAQ

Questions LlamaCloud owners ask.

01
How do I connect LlamaCloud to my AI agent?
You subscribe to the MCP on Vinkius and enter your LlamaCloud API Key. Once connected, you can use it immediately in any MCP-compatible client.
02
Can I parse complex PDFs with this MCP?
Yes. You can use the create_parsing_upload capability to send PDFs to LlamaParse, which converts tables and complex layouts into Markdown.
03
What clients are compatible with this MCP?
This MCP works with any compatible client, including Claude, Cursor, Windsurf, and VS Code.
04
How do I check if a parsing job is finished?
You can use the list_parsing_jobs capability to see active jobs or use get_parsing_result to pull the final data once it is complete.
05
Do I need to write code to manage my pipelines?
No. You can list pipelines, get configurations, and manage projects using natural language commands through your AI agent.
06
Can LlamaParse handle complex tables and layouts in my PDFs?
Absolutely. LlamaParse uses AI-driven parsing to turn complex PDF layouts, nested tables, and even handwriting into structured Markdown. Use the create_parsing_upload capability to start the process and retrieve high-quality context for your agent.
07
How do I check if my RAG data pipeline is finished processing?
Use the get_parsing_result capability with your specific Job ID. Your agent will poll the LlamaCloud API and report the current status. Once finished, it will retrieve the final parsed content ready for grounding.
08
Can I see all data sources connected to a specific pipeline?
Yes. The get_pipeline capability extracts the full configuration for any pipeline ID, identifying all connected data sources and configured index settings, ensuring you have a complete view of your ingestion flow.

Explore

More in AI Frontier

Connect LlamaCloud to Claude, Cursor, ChatGPT & more

Your AI does the work. We keep it safe and sound.

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-03

List pipelines

Get pipeline

List projects

04-06

List parsing jobs

Create parsing upload

Get parsing result

What teams actually run

Automated Document Ingestion

RAG Pipeline Auditing

Data Integrity Checks

Real-time Job Tracking

Building your own app? The connector is yours to use.

LlamaCloud Connector

Claude Desktop

RAG Developers

AI Engineers

Data Scientists

How do I connect LlamaCloud to my AI agent?

Can I parse complex PDFs with this MCP?

What clients are compatible with this MCP?

How do I check if a parsing job is finished?

Do I need to write code to manage my pipelines?

Can LlamaParse handle complex tables and layouts in my PDFs?

How do I check if my RAG data pipeline is finished processing?

Can I see all data sources connected to a specific pipeline?

Hevo Data (ETL & Data Pipeline) AI Connector

Integrate.io (ETL & Data Integration) AI Connector

MyScale (SQL Vector Database API) AI Connector

Dataiku DSS AI Connector

Suggestions

Data Pipeline Prover AI Connector

Cognita (RAG Framework) AI Connector

Airbyte AI Connector

data.world AI Connector