Digify MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Digify as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Digify. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Digify?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Digify MCP Server
Integrate Digify, the leading document security and virtual data room (VDR) platform, directly into your AI workflow. Manage your secure files, monitor data room activity, and track detailed document analytics using natural language.
LlamaIndex agents combine Digify tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Secure File Oversight — List and retrieve detailed information and security settings for all your protected files.
- VDR Management — Monitor your virtual data rooms, including member lists and collaborative activity.
- Engagement Analytics — Retrieve detailed statistics on who viewed your files, for how long, and from where.
- Access Control — List recipients and monitor their specific viewing rights and permissions for secure assets.
The Digify MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Digify to LlamaIndex via MCP
Follow these steps to integrate the Digify MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Digify
Why Use LlamaIndex with the Digify MCP Server
LlamaIndex provides unique advantages when paired with Digify through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Digify tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Digify tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Digify, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Digify tools were called, what data was returned, and how it influenced the final answer
Digify + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Digify MCP Server delivers measurable value.
Hybrid search: combine Digify real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Digify to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Digify for fresh data
Analytical workflows: chain Digify queries with LlamaIndex's data connectors to build multi-source analytical reports
Digify MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Digify to LlamaIndex via MCP:
get_dataroom_details
Get detailed settings and member lists for a specific data room
get_file_access_statistics
Retrieve detailed analytics on who viewed your file and for how long
get_secure_file_details
Get detailed information and security settings for a specific file
get_security_account_metadata
Retrieve metadata and usage limits for your Digify account
list_expired_secure_files
Identify secure files that have reached their expiration date (mock logic)
list_file_recipients
List all people who have been granted access to a specific secure file
list_secure_files
List all secure files you have uploaded to Digify
list_virtual_datarooms
List all virtual data rooms (VDRs) in your account
quick_file_audit
Retrieve a high-level summary of file views and security rights
search_secure_files
Search for secure files by filename keyword
Example Prompts for Digify in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Digify immediately.
"List all secure files I've uploaded."
"Who has viewed the 'M&A Proposal' file and for how long?"
"Show me the details for our 'Investor Data Room'."
Troubleshooting Digify MCP Server with LlamaIndex
Common issues when connecting Digify to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDigify + LlamaIndex FAQ
Common questions about integrating Digify MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Digify with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Digify to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.