How to Use the Filemail MCP in LlamaIndex

Q: How do I index my Filemail transfer logs in LlamaIndex?

You run the MCP tool listsenttransfers to fetch your transfer history. LlamaIndex then parses these logs into document nodes and inserts them into your vector index.

Q: Can LlamaIndex check Filemail transfer details during a query?

Yes, the agent can call gettransferdetails dynamically if the indexed data doesn't answer the user's question. This combines historical vector search with live API checks.

Index your Filemail transfer history via our MCP Server into LlamaIndex to query your delivery data with natural language.

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Connect Filemail MCP to LlamaIndex

Create your Vinkius account to connect Filemail 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 Filemail with LlamaIndex

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Index Filemail Transfer Records into LlamaIndex RAG

LlamaIndex turns your transfer history into a searchable knowledge base. By calling `list_sent_transfers` and `list_received_transfers`, the framework pulls metadata and indexes it directly into your vector store. This stops you from digging through old emails to find out when a client downloaded a file. You just ask your agent, and it queries the index to find the exact timestamp from `get_transfer_details`.

Query Your Contact List with Semantic Search

Instead of scrolling through endless lists, use natural language to find recipients. Your agent calls `list_contacts` to retrieve your address book and indexes the names and emails. You can ask your agent to find contacts who receive files frequently. The system matches your query against the indexed profile data retrieved from `get_user` to give you instant answers.

Monitor Account Configuration and Limits in Real Time

Keep your document pipelines grounded in your actual account constraints. The agent pulls your active settings via `get_configuration` to index your current transfer limits and branding choices. This prevents your agent from attempting transfers that exceed your plan. It checks the indexed configuration before running `initialize_transfer`, avoiding API errors and keeping operations within bounds.

Setup guide

Set up Filemail 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 Filemail 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 Filemail tools.",
)
response = await agent.run("List recent Filemail 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 Filemail. 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 Filemail MCP in LlamaIndex

You run the MCP tool `list_sent_transfers` to fetch your transfer history. LlamaIndex then parses these logs into document nodes and inserts them into your vector index.

Yes, the agent can call `get_transfer_details` dynamically if the indexed data doesn't answer the user's question. This combines historical vector search with live API checks.

Yes, the server exposes resources that LlamaIndex can read. This allows the framework to pull your user profile via `get_user` directly into its context.

You can use LlamaIndex's tool filtering to only allow specific tools like `list_received_transfers`. This ensures you only index incoming files and ignore outgoing ones.

Your user profiles and contact emails are kept local. The server processes all data inside a zero-trust sandbox, so your recipient lists are never shared or stored externally.

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