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How to Use the NS1 (IBM NS1 Premium DNS API) MCP in LlamaIndex

Index your live DNS state into LlamaIndex for grounded, queryable infrastructure knowledge using the NS1 (IBM NS1 Premium DNS API) MCP Server.

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Connect NS1 (IBM NS1 Premium DNS API) MCP to LlamaIndex

Create your Vinkius account to connect NS1 (IBM NS1 Premium DNS API) 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.

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Index DNS metadata in LlamaIndex

Transform your DNS records into searchable knowledge by indexing the output of `get_zone` and `get_record`. This allows your RAG application to answer questions about your current infrastructure configuration based on live data. Instead of relying on outdated documentation, your system queries the actual source of truth. The agent retrieves the current state, and LlamaIndex stores it, providing a consistent view of your global records.

Search monitoring jobs with LlamaIndex

Feed the results of `list_monitoring_jobs` into your vector store to keep a history of your infrastructure's health checks. Your application can query this data to see how monitoring coverage has changed over time. This approach grounds your AI responses in real API data. When you ask about your current monitoring setup, the agent provides facts retrieved directly from the IBM NS1 platform.

Semantic DNS management in LlamaIndex

Combine your technical documentation with live data from `list_zones` to create a unified knowledge base. This lets your agent provide context-aware answers that include current zone configurations. You can then use the agent to perform maintenance tasks based on these queries. It finds the zone details and suggests actions, which you can then execute using the provided tools.

Setup guide

Set up NS1 (IBM NS1 Premium DNS API) MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 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. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all NS1 (IBM NS1 Premium DNS API) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 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 NS1 (IBM NS1 Premium DNS API) tools.",
)
response = await agent.run("List recent NS1 (IBM NS1 Premium DNS API) data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by NS1 (IBM NS1 Premium DNS API). 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 NS1 (IBM NS1 Premium DNS API) MCP in LlamaIndex

Use the MCP tool spec client to bridge the connection. Once indexed, your agents can perform semantic searches across your live DNS records and monitoring jobs.
Yes. The server allows your agent to fetch specific records, which are then passed into the vector store for querying alongside your existing documents.
You can use the allowed_tools filter to restrict which DNS operations your agent can perform. This prevents the agent from modifying zones unless specifically authorized.
By fetching the latest record details, the agent ensures its answers are based on the current state of your DNS. This avoids the risk of hallucinating about outdated infrastructure.
Your DNS zone names and record values are indexed locally within your agent's vector store. The server treats this data as sensitive, and it is never shared beyond your specific LlamaIndex implementation.

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