How to Use the Documo MCP in LlamaIndex

Q: How do I index Documo fax records into LlamaIndex?

You use the McpToolSpec to register the listdigitalfaxes tool with your LlamaIndex agent. The agent pulls the metadata from your faxes and indexes the transmission records directly into your vector database.

Q: Can LlamaIndex search Documo records by recipient?

Yes, the agent uses searchfaxesbyrecipient to find specific matches based on a phone number or identifier. It then indexes those results to answer targeted questions about that recipient's history.

Q: How does LlamaIndex use Documo account metadata?

Your agent calls getdocumoaccountmetadata to verify your plan limits before running heavy indexing jobs. This ensures your RAG pipeline stays within safe operational boundaries without hitting API blocks.

Q: Can I track received faxes inside my index?

The agent uses listreceiveddigitalfaxes to fetch incoming documents and add them to your index. This keeps your searchable knowledge base updated with the latest incoming files in near real-time.

Index Documo fax metadata into your LlamaIndex vector store to run semantic search over your entire transmission history.

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Connect Documo MCP to LlamaIndex

Create your Vinkius account to connect Documo 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 Documo with LlamaIndex

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Index active Documo lines into LlamaIndex

Your LlamaIndex agent calls `list_assigned_fax_numbers` to pull your active lines and index them into a searchable document store. This lets you query your fax infrastructure using plain English instead of searching through spreadsheets. By registering this MCP Server with LlamaIndex, your agent immediately knows which line handles which department. You don't have to hardcode routing rules when a new number is added to your account.

Ground RAG queries in real Documo transmission data

The `list_latest_fax_transmissions` tool feeds recent activity directly into your LlamaIndex query engine to ground agent responses in live data. This stops your agent from hallucinating about whether a critical document arrived. When a user asks about a pending document, the agent pulls the latest logs, updates its local index, and provides an accurate status report. It links the query to the exact timestamps and status codes found in your account.

Audit volume metrics using this MCP Server

The `quick_fax_volume_audit` tool gives your LlamaIndex pipeline a structured summary of success rates and transmission volumes. The agent indexes these audit summaries to track performance trends over weeks or months. Instead of parsing raw log files, you query the MCP Server to generate instant reports on delivery performance. You get clear, data-backed answers about your transmission health without writing complex database queries.

Setup guide

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

You use the McpToolSpec to register the `list_digital_faxes` tool with your LlamaIndex agent. The agent pulls the metadata from your faxes and indexes the transmission records directly into your vector database.

Yes, the agent uses `search_faxes_by_recipient` to find specific matches based on a phone number or identifier. It then indexes those results to answer targeted questions about that recipient's history.

Your agent calls `get_documo_account_metadata` to verify your plan limits before running heavy indexing jobs. This ensures your RAG pipeline stays within safe operational boundaries without hitting API blocks.

The agent uses `list_received_digital_faxes` to fetch incoming documents and add them to your index. This keeps your searchable knowledge base updated with the latest incoming files in near real-time.

Your transmission metadata and account credentials are protected by Vinkius's zero-trust architecture. All tool executions run in isolated, ephemeral environments, meaning your fax numbers and transmission logs are never written to persistent disk.

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