How to Use the Convertio MCP in LlamaIndex

Q: How does LlamaIndex handle converted file formats?

The server provides a list of supported formats via listcommonformats. Your agent can check this list before choosing an output type.

Index your converted documents into LlamaIndex for semantic search and grounded retrieval.

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Connect Convertio MCP to LlamaIndex

Create your Vinkius account to connect Convertio 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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Setup Convertio with LlamaIndex

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Convert documents for LlamaIndex RAG

Use `quick_convert_to_pdf` to transform raw web documents into text-rich files. This makes them ready for your vector store. Your agent converts the file, and LlamaIndex indexes the text immediately. You get a searchable knowledge base built from live file data.

Index file status in LlamaIndex

Query `get_conversion_status` and add the result to your index. This allows your agent to answer questions about the state of your library. You no longer guess if a file is ready. The agent knows exactly where your documents stand by checking the MCP Server directly.

Manage your conversion library

Use `delete_conversion_job` to purge files you no longer need. This keeps your index clean and relevant. Your agent maintains your storage footprint. It removes unnecessary records automatically to keep your LlamaIndex retrieval fast.

Setup guide

Set up Convertio MCP in LlamaIndex

Prerequisites

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

1

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

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Convertio MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
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 Convertio tools.",
)
response = await agent.run("List recent Convertio data")

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Common questions about Convertio MCP in LlamaIndex

Install the MCP tool spec, initialize the client with our URL, and pass the tools to your agent. This grants your agent full access to the conversion suite.

By indexing the results of your past jobs, LlamaIndex turns your history into a searchable database. You can ask about past conversions naturally.

Yes, you can restrict which tools your agent accesses. This limits the agent to specific formats or actions as defined in your tool list.

The server provides a list of supported formats via `list_common_formats`. Your agent can check this list before choosing an output type.

We isolate all conversion jobs in a sandbox. Only the converted text that you explicitly index is stored in your local vector database.

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