Egnyte MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Folder, Create Shared Link, Delete Item, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Egnyte 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 App Connector for LlamaIndex
The Egnyte app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Egnyte. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Egnyte?"
)
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 Egnyte MCP Server
Connect your Egnyte enterprise account to any AI agent and take full control of your corporate file sync and share (EFSS) workflows through natural conversation.
LlamaIndex agents combine Egnyte tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Content Orchestration — List and manage files and folders programmatically, including creating new directories and retrieving detailed metadata
- Secure Sharing — Programmatically generate shared links with customizable accessibility (public, password, domain) directly from your agent
- Deep Semantic Search — Find relevant files and folders across your entire domain using advanced text queries and filters
- User & Group Visibility — Retrieve complete directories of users and groups to coordinate permissions and team collaboration
- Compliance Monitoring — Access security audit logs and monitor active webhooks to maintain high-fidelity oversight of your corporate data
The Egnyte MCP Server exposes 12 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.
All 12 Egnyte tools available for LlamaIndex
When LlamaIndex connects to Egnyte through Vinkius, your AI agent gets direct access to every tool listed below — spanning egnyte, cloud-storage, file-sync, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new folder
Generate share link
Delete file or folder
Get domain info
List audit events
Get file details
List folder contents
List user groups
List all shared links
List Egnyte users
List active webhooks
Search for files
Connect Egnyte to LlamaIndex via MCP
Follow these steps to wire Egnyte into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Egnyte MCP Server
LlamaIndex provides unique advantages when paired with Egnyte through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Egnyte tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Egnyte tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Egnyte, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Egnyte tools were called, what data was returned, and how it influenced the final answer
Egnyte + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Egnyte MCP Server delivers measurable value.
Hybrid search: combine Egnyte real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Egnyte 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 Egnyte for fresh data
Analytical workflows: chain Egnyte queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Egnyte in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Egnyte immediately.
"List all files in the folder '/Shared/Projects/MCP'."
"Search for documents containing '2026 marketing budget'."
"Show me the last 5 security audit logs."
Troubleshooting Egnyte MCP Server with LlamaIndex
Common issues when connecting Egnyte to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpEgnyte + LlamaIndex FAQ
Common questions about integrating Egnyte MCP Server with LlamaIndex.