How to Use the Cloudify MCP in LlamaIndex

Q: Does Cloudify work with LlamaIndex filters?

You can use the allowedtools filter to restrict which infrastructure data the agent can access. This keeps your index focused on relevant deployment information.

Index your Cloudify infrastructure data into LlamaIndex for searchable, grounded cloud intelligence.

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Connect Cloudify MCP to LlamaIndex

Create your Vinkius account to connect Cloudify 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 Cloudify with LlamaIndex

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Index Cloudify schemas in LlamaIndex

Pass `list_blueprints` results into your vector store to build a searchable knowledge base. Your agent stops hallucinating about infrastructure because it queries the indexed blueprint data. This turns static configuration files into a queryable resource. You ask questions about your architecture, and the agent pulls the right answers from the index.

Ground LlamaIndex queries with Cloudify

Use `get_deployment` to fetch internal structural states for your RAG applications. The agent grounds its reasoning in the specific topology of your live deployments. Every search result reflects current reality rather than outdated documentation. Your RAG pipeline becomes a source of truth for your cloud operations.

Search node limits with LlamaIndex

Retrieve `list_nodes` output to understand exact routing rules and instance limits. By indexing this data, you make your infrastructure metadata available for semantic search. Your agent interprets the context of these nodes during its analysis. It provides answers based on the actual configuration of your cluster.

Setup guide

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

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Common questions about Cloudify MCP in LlamaIndex

Initialize the MCP tool spec and convert the output to a tool list. Once added to your agent, it automatically indexes the results for semantic search.

You can use the allowed_tools filter to restrict which infrastructure data the agent can access. This keeps your index focused on relevant deployment information.

We use scoped tokens to ensure the MCP server only interacts with authorized data. Your infrastructure details are never exposed to external models without your explicit permission.

You can configure the client to pull from various sources. The index then merges these into a unified view for your agent to query.

The server shares deployment topologies, node limits, and plugin metadata. This information is processed in a transient sandbox and protected by our zero-trust architecture.

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