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How to Use the Cloud BOT MCP in LlamaIndex

Turn web automation results into searchable knowledge for LlamaIndex by indexing Cloud BOT output into your vector store.

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Works with every AI agent you already use

…and any MCP-compatible client

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LlamaIndex

Connect Cloud BOT MCP to LlamaIndex

Create your Vinkius account to connect Cloud BOT to LlamaIndex 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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Index Cloud BOT data in LlamaIndex

Run `execute_bot` and feed the results into your vector index. It grounds your agent's answers in live web data. Your LlamaIndex application treats the output as a new document. You query this data later to find patterns in your automated browser tasks.

Search job history in LlamaIndex

Use `list_jobs` to pull recent execution history into your knowledge base. It makes your past browser interactions queryable. You avoid hallucinations by grounding your answers in actual API logs. The agent pulls the history, indexes it, and answers your questions based on facts.

Automate bot discovery for RAG

Map out your available bots with `list_bots` and build a searchable registry. Your agent knows exactly which bot to call for a specific query. This creates a self-documenting system. You ask your agent to find data, and it references the indexed bot list to choose the right tool.

Setup guide

Set up Cloud BOT MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 2

    Connect with BasicMCPClient

    Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.

  3. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all Cloud BOT MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 4

    Run with any LLM

    Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

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

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Cloud BOT tools.",
)
response = await agent.run("List recent Cloud BOT data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cloud BOT. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Real-time monitoring

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visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Cloud BOT MCP in LlamaIndex

You wrap the tools in a spec and pass them to your FunctionAgent. The tools become native functions your index can call.
It provides structured output that gets converted into searchable nodes. Your agent uses these to retrieve relevant information during a query.
You can use the allowed_tools filter to limit which functions the agent sees. This keeps your index focused on specific tasks.
No, because the agent retrieves the actual output from your recent jobs. It uses the API data as the source of truth.
Only the job status and task output you choose to index are stored. We ensure that sensitive browser cookies or form inputs remain isolated.

Start using the Cloud BOT MCP today

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Built & Managed by Vinkius 30s setup 7 tools

We've already built the connector for Cloud BOT. Just plug in your AI agents and start using Vinkius.

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