How to Use the Censys MCP in LlamaIndex

Q: How do I index Censys host data with LlamaIndex?

You wrap the Censys tools in a McpToolSpec and pass them to a LlamaIndex agent. When the agent calls searchhosts or gethost, the tool's output can be directed into your vector store, creating embeddings from the host data.

Q: Can I use LlamaIndex to ask questions about my Censys certificate inventory?

Absolutely. First, use the searchcertificates tool to populate an index with all your certificate data. Then you can ask your LlamaIndex RAG application natural language questions about expiration dates, issuers, or key algorithms.

Turn raw Censys data into a searchable knowledge base with your LlamaIndex RAG apps.

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Connect Censys MCP to LlamaIndex

Create your Vinkius account to connect Censys 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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Setup Censys with LlamaIndex

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Build a Queryable Host Inventory

Don't just run a scan. Build an index. Use the `search_hosts` and `get_host` tools to feed data directly into a LlamaIndex vector store. Every IP, port, and service banner becomes a searchable piece of knowledge about your network. Once it's indexed, you can ask natural language questions. 'Which of our servers are still running an old version of nginx?' LlamaIndex finds the answer from the Censys data you've already collected. This MCP Server gives you the live data; LlamaIndex makes it part of your long-term memory.

Index Your Certificate Landscape

Your certificate inventory is now a queryable database. Point the `search_certificates` tool at LlamaIndex to ingest every certificate you own. The tool's output—subjects, issuers, and validity dates—is indexed automatically. This means you can ask 'Show me all certificates expiring in the next 30 days' and get a straight answer grounded in real data. You can even follow up by using `get_certificate_hosts` to find the exact machines that need attention, adding that context back into your index.

Ask Questions About Infrastructure Trends

The `aggregate_hosts` tool is perfect for high-level analysis. You can group hosts by country, by open port, or by operating system. Instead of just getting a list, you get a summary of your global footprint. Feed these aggregations into LlamaIndex. Now you can ask things like, 'What are the top 5 countries where our assets are located?' or 'What's the most common port we have open to the internet?' LlamaIndex retrieves the answers from the indexed Censys aggregation data, giving you instant business intelligence.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Censys. 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 Censys MCP in LlamaIndex

You wrap the Censys tools in a `McpToolSpec` and pass them to a LlamaIndex agent. When the agent calls `search_hosts` or `get_host`, the tool's output can be directed into your vector store, creating embeddings from the host data.

Absolutely. First, use the `search_certificates` tool to populate an index with all your certificate data. Then you can ask your LlamaIndex RAG application natural language questions about expiration dates, issuers, or key algorithms.

Censys finds the data; LlamaIndex makes it knowledge. By indexing the results from this MCP Server, you're not just getting a point-in-time snapshot. You're building a memory that lets you query and correlate findings over time.

You can add a transformation layer in your LlamaIndex application. Before the output of a Censys tool is indexed, you can write a simple function to select, clean, or reformat the JSON to fit your exact needs.

The server only handles public host and certificate information from Censys. Your queries are sent through a secure, isolated Vinkius environment for this MCP integration. No private keys or internal network data are ever exposed.

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