How to Use the Cockpit (Self-hosted Headless CMS API) MCP in LlamaIndex

Index your Cockpit (Self-hosted Headless CMS API) content directly into LlamaIndex for RAG.

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Connect Cockpit (Self-hosted Headless CMS API) MCP to LlamaIndex

Create your Vinkius account to connect Cockpit (Self-hosted Headless CMS 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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Setup Cockpit (Self-hosted Headless CMS API) with LlamaIndex

Ask AI about this MCP

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Claude

Perplexity

Build RAG from CMS data

Use `list_content_items` to pull your entire collection into a searchable vector store. LlamaIndex then converts these records into embeddings for semantic retrieval. Your agent now answers questions grounded in your actual site content. It stops guessing and starts citing your specific CMS records.

Search and fetch with LlamaIndex

The `search_detektivo` tool lets your agent query specific indexes inside your CMS. This returns precise matches that LlamaIndex can immediately add to its knowledge base. It turns your static CMS into a dynamic knowledge source. Your agent queries the API, indexes the result, and provides an answer in one go.

Deep asset integration

Fetch image metadata with `get_asset` and include it in your knowledge index. Your agent can then reason about site assets alongside your text content. This gives your agent a complete picture of your site. It understands both the copy and the visual elements defined in the CMS.

Setup guide

Set up Cockpit (Self-hosted Headless CMS API) 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 Cockpit (Self-hosted Headless CMS API) 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 Cockpit (Self-hosted Headless CMS API) tools.",
)
response = await agent.run("List recent Cockpit (Self-hosted Headless CMS API) 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 Cockpit CMS. 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 Cockpit (Self-hosted Headless CMS API) MCP in LlamaIndex

You initialize the client, retrieve the tool list, and pass those functions to your agent. From there, the agent pulls the data and adds it to your vector store.

No, because the agent retrieves the data in real-time. By grounding its responses in your actual CMS entries, it avoids making things up.

You can. Use the menu tools to pull your navigation structure, which LlamaIndex then treats as part of your site's searchable context.

You control the refresh cycle. Since the agent fetches live data, you can trigger a re-index whenever you update your content items.

The server uses an ephemeral connection between your agent and your private CMS instance. No CMS content is cached or stored by us during the indexing process.

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