How to Use the Files.com MCP in LlamaIndex

Q: How do I filter Files.com data in LlamaIndex?

Use the allowedtools filter in your client config. This restricts the agent to specific operations, ensuring it only interacts with the data you specify.

Index your Files.com data with LlamaIndex. Create searchable knowledge bases from file activity and directory structures.

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Connect Files.com MCP to LlamaIndex

Create your Vinkius account to connect Files.com 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 Files.com with LlamaIndex

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Index Files.com metadata for search

Feed output from `list_folders` and `get_file_details` into your vector store. Your LlamaIndex agents can then query this index to find files based on their actual location and properties. This turns your static file storage into a queryable data source. You no longer have to guess where a file lives when you can ask your agent to retrieve it.

Ground AI answers in real-time data

Stop hallucinating file locations by using `list_activity_history` to provide context for your RAG pipeline. Your agents access live logs to answer questions about recent changes. This creates a grounded knowledge base that reflects current system states. Your agents can explain exactly when a file was modified or deleted based on actual API data.

Map permissions for semantic context

Use `list_permissions` and `list_user_groups` to index access policies alongside your files. Your LlamaIndex setup can then filter search results based on user access levels. This ensures that your agent only provides information the user is allowed to see. It ties your security model directly into your retrieval strategy.

Setup guide

Set up Files.com 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 Files.com 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 Files.com tools.",
)
response = await agent.run("List recent Files.com data")

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

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Common questions about Files.com MCP in LlamaIndex

The MCP server provides the data via standard tool calls. LlamaIndex then ingests this data into your vector store for semantic retrieval.

Absolutely, once you connect the server, you can use natural language to ask about file activity. The agent calls the relevant tools to gather the facts.

You control the refresh rate of your index. Trigger a new scan using `list_folders` to update your knowledge base with the latest directory changes.

Use the allowed_tools filter in your client config. This restricts the agent to specific operations, ensuring it only interacts with the data you specify.

The server uses a zero-trust architecture. Your file metadata and user records are never exposed to third parties, only indexed within your local vector store.

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