UpGuard MCP Server for LlamaIndexGive LlamaIndex instant access to 9 tools to Get Vendor, List Account Risks, List Identity Breaches, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add UpGuard 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 for LlamaIndex
The UpGuard MCP Server for LlamaIndex is a standout in the Fort Knox category — giving your AI agent 9 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 UpGuard. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in UpGuard?"
)
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 UpGuard MCP Server
Connect your UpGuard account to any AI agent and simplify how you monitor your attack surface, assess third-party vendor risks, and protect your organization's digital assets through natural conversation.
LlamaIndex agents combine UpGuard tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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
- Vendor Risk Assessment — List and query all monitored vendors to retrieve their security scores and metadata.
- Risk Monitoring — List active security risks detected across your own infrastructure (BreachSight) and your vendor network (VendorRisk).
- Data Breach Tracking — Monitor identity breaches affecting your workforce and retrieve detailed breach reports.
- Asset Visibility — List monitored domains, IP ranges, and SaaS applications to understand your digital footprint.
- Employee Security — Audit user-related risk data and identity theft exposures directly via AI commands.
The UpGuard MCP Server exposes 9 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 9 UpGuard tools available for LlamaIndex
When LlamaIndex connects to UpGuard through Vinkius, your AI agent gets direct access to every tool listed below — spanning attack-surface, vendor-risk, cybersecurity, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Get vendor on UpGuard
Get details for a specific vendor
List account risks on UpGuard
List all active risks for the account
List identity breaches on UpGuard
List identity breaches
List monitored domains on UpGuard
List monitored domains
List monitored ips on UpGuard
List monitored IP addresses
List saas apps on UpGuard
List monitored SaaS applications
List user risks on UpGuard
List users and their risk data
List vendor risks on UpGuard
List active risks for a vendor
List vendors on UpGuard
List all monitored vendors
Connect UpGuard to LlamaIndex via MCP
Follow these steps to wire UpGuard into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind 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 UpGuard MCP Server
LlamaIndex provides unique advantages when paired with UpGuard through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine UpGuard tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain UpGuard tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query UpGuard, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what UpGuard tools were called, what data was returned, and how it influenced the final answer
UpGuard + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the UpGuard MCP Server delivers measurable value.
Hybrid search: combine UpGuard real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query UpGuard 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 UpGuard for fresh data
Analytical workflows: chain UpGuard queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for UpGuard in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with UpGuard immediately.
"List all monitored vendors and their security scores."
"Show me the active risks for the vendor 'Microsoft'."
"Are there any recent identity breaches affecting our domain?"
Troubleshooting UpGuard MCP Server with LlamaIndex
Common issues when connecting UpGuard to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpUpGuard + LlamaIndex FAQ
Common questions about integrating UpGuard 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?
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