How to Use the HetrixTools MCP in LlamaIndex
Index your live server status and blacklist reports directly into your LlamaIndex knowledge base.
Works with every AI agent you already use
…and any MCP-compatible client
Connect HetrixTools MCP to LlamaIndex
Create your Vinkius account to connect HetrixTools 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.
Index Server Health Logs for RAG
This MCP Server provides the `list_uptime_reports` tool to feed raw historical performance data directly into your LlamaIndex vector store. Your agent queries this indexed data to spot long-term latency trends that simple alerts miss. By indexing the output of `list_uptime_monitors`, LlamaIndex builds a searchable map of your infrastructure. When a user asks about system health, the agent retrieves the exact status from the index instead of guessing.
Search IP Reputation History in LlamaIndex
The `check_ip_blacklist` tool lets your LlamaIndex agent run live reputation checks and index the results instantly. This prevents mail delivery issues by keeping a searchable history of IP health in your local vector database. You can query past blacklist events by feeding `list_blacklist_monitors` and `check_domain_blacklist` outputs into your index. Semantic search helps the agent find which domains have a history of failing spam filters.
Manage Uptime Configurations with RAG
The `add_uptime_monitor` tool allows your LlamaIndex agent to configure new targets using our MCP Server. It looks up contact IDs with `list_contact_lists` to set up the new monitor correctly. If a monitor is misconfigured, the agent calls `delete_uptime_monitor` after verifying the error against your indexed setup guides. You can also track your API limits by indexing `get_account_usage` to avoid unexpected service interruptions.
Set up HetrixTools MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - 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 providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto 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 HetrixTools MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
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 HetrixTools tools.",
)
response = await agent.run("List recent HetrixTools data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HetrixTools. 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 HetrixTools MCP in LlamaIndex
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the HetrixTools MCP today
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