How to Use the Cincopa MCP in LlamaIndex

Q: How do I connect the Cincopa MCP Server to LlamaIndex?

Install llama-index-tools-mcp and initialize BasicMCPClient with your Vinkius URL. Wrap it in McpToolSpec and convert it using mcptoolspec.totoollistasync() for your FunctionAgent.

Q: Can LlamaIndex index Cincopa video metadata for semantic search?

Yes, it can. The agent calls listcincopaassets and getassetmetadata to retrieve details like video descriptions, tags, and dimensions, then indexes them into your vector store.

Q: Does LlamaIndex support real-time Cincopa gallery creation?

Yes. Your agent can use createnewgallery to build a gallery when a search query reveals that a requested media collection does not exist yet.

Q: How can I limit which Cincopa tools LlamaIndex can access?

You can use the allowedtools filter during initialization of your MCP client. This prevents the agent from running destructive actions like deletemediaasset while still allowing asset listing.

Index Cincopa video metadata and gallery structures into LlamaIndex to build searchable, media-aware RAG applications.

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Connect Cincopa MCP to LlamaIndex

Create your Vinkius account to connect Cincopa 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 Cincopa with LlamaIndex

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Turn Cincopa asset data into LlamaIndex vector stores

Stop guessing which video contains the content you need. This MCP Server allows LlamaIndex to fetch raw media information via `list_cincopa_assets` and index it directly into your vector database for semantic search. By feeding the output of `get_asset_metadata` into your index, your RAG application can answer complex queries about your video library. Your agent retrieves actual technical specs and engagement metrics instead of making assumptions.

Query live Cincopa gallery details using RAG

Your LlamaIndex search queries can now span live gallery layouts and active designs. By calling `get_gallery_details` and `list_cincopa_galleries`, your agent pulls real-time configuration data to ground its answers. This setup eliminates outdated information. When a user asks which galleries use a specific style, the agent queries `list_cincopa_templates` and matches it against live data, ensuring 100% accurate responses.

Automate Cincopa media uploads via LlamaIndex agents

LlamaIndex agents do more than search; they can execute file management tasks. The agent requests a temporary upload endpoint using `get_media_upload_url` and coordinates the ingest process based on current index gaps. If your knowledge base detects missing assets, the agent can clean up redundant files with `delete_media_asset`. This keeps your Cincopa storage optimized and your search index perfectly synchronized.

Setup guide

Set up Cincopa 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 Cincopa 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 Cincopa tools.",
)
response = await agent.run("List recent Cincopa 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 Cincopa. 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 Cincopa MCP in LlamaIndex

Install `llama-index-tools-mcp` and initialize `BasicMCPClient` with your Vinkius URL. Wrap it in `McpToolSpec` and convert it using `mcp_tool_spec.to_tool_list_async()` for your FunctionAgent.

Yes, it can. The agent calls `list_cincopa_assets` and `get_asset_metadata` to retrieve details like video descriptions, tags, and dimensions, then indexes them into your vector store.

Yes. Your agent can use `create_new_gallery` to build a gallery when a search query reveals that a requested media collection does not exist yet.

You can use the `allowed_tools` filter during initialization of your MCP client. This prevents the agent from running destructive actions like `delete_media_asset` while still allowing asset listing.

Vinkius processes all tool requests, like fetching gallery structures or asset metadata, in isolated, ephemeral sandboxes. No media files or Cincopa account credentials are saved to disk, keeping your video library secure.

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