How to Use the IP Address Parser MCP in LlamaIndex

Q: Can LlamaIndex store the outputs of the IP Address Parser?

Yes, you can index the structured JSON returned by parseipaddress directly into your vector store. This allows your LlamaIndex agent to perform semantic searches over parsed network metadata like CIDR ranges and IP families.

Q: Does this tool support IPv4 to IPv6 mapping within LlamaIndex?

The parseipaddress tool handles IPv4-mapped IPv6 addresses, letting your LlamaIndex agent normalize different IP representations before storing them in your index.

Index network data and query parsed IP metadata within your LlamaIndex RAG applications.

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Connect IP Address Parser MCP to LlamaIndex

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Setup IP Address Parser with LlamaIndex

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Index parsed IP metadata into LlamaIndex vector stores

Feed your security logs into LlamaIndex and let the agent parse IP addresses into structured metadata. The `parse_ip_address` tool extracts the family, range, and CIDR masks, allowing you to index this structured data right alongside your raw log text. This structured indexing prevents your LLM from hallucinating IP classes. Instead of guessing if an IP is private or public, your RAG pipeline queries the vector store and retrieves verified IP metadata parsed directly by this MCP Server.

Build network-aware RAG pipelines

Give your LlamaIndex query engine the ability to resolve IP subnets on the fly. When a user asks about traffic from a specific subnet, the engine calls `parse_ip_address` to verify the range before searching your indexed documents. This live validation ensures that search queries are grounded in accurate network schemas. Your agent won't waste tokens searching for invalid IP formats or mismatched subnet ranges because the tool filters them out first.

Structured query filters for security logs

Convert raw IP strings into queryable metadata filters within LlamaIndex. The agent runs `parse_ip_address` on incoming queries, extracts the IP family or range type, and uses those attributes to narrow down the vector search space. This approach speeds up retrieval times for massive log datasets. By filtering by verified IP properties before executing semantic search, you get faster, more accurate answers to complex security questions.

Setup guide

Set up IP Address Parser 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 IP Address Parser 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 IP Address Parser tools.",
)
response = await agent.run("List recent IP Address Parser data")

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Common questions about IP Address Parser MCP in LlamaIndex

Use the LlamaIndex MCP tool spec package to connect to your Vinkius endpoint URL. Convert the server tools to a list of llama-index tools and pass them to your FunctionAgent to enable the `parse_ip_address` tool.

Yes, you can index the structured JSON returned by `parse_ip_address` directly into your vector store. This allows your LlamaIndex agent to perform semantic searches over parsed network metadata like CIDR ranges and IP families.

Instead of letting the LLM guess if an IP is public or private, the agent calls `parse_ip_address` to get concrete validation data. This ensures your LlamaIndex RAG system relies on strict RFC-compliant parsing rather than language model heuristics.

The `parse_ip_address` tool handles IPv4-mapped IPv6 addresses, letting your LlamaIndex agent normalize different IP representations before storing them in your index.

All IP strings and CIDR blocks processed by this MCP Server run inside zero-trust, isolated V8 containers. Vinkius handles the underlying infrastructure securely, meaning your sensitive network configurations never touch persistent disks or external storage.

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