How to Use the Gumlet MCP in LlamaIndex

Q: How do I index Gumlet asset metadata in LlamaIndex?

Use the llama-index-tools-mcp package to load the tools into your agent. The agent calls listvideos to fetch the metadata and inserts it directly into your vector database.

Q: Can LlamaIndex query live Gumlet video performance data?

Yes, by using the getvideoanalytics tool within a query engine. The agent pulls live statistics during the retrieval step to ground its answers in real-time performance.

Q: Does the Gumlet integration with LlamaIndex support the MCP Server protocol?

It does when you index the output of tools like listvideocollections. This lets your agent locate the right folder using natural language queries.

Build media-aware RAG pipelines in LlamaIndex by indexing Gumlet video analytics and image source configurations.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Gumlet MCP to LlamaIndex

Create your Vinkius account to connect Gumlet 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.

GDPR Free for Subscribers

Setup Gumlet with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Turn CDN data into searchable knowledge

The `get_video_analytics` tool retrieves live viewer engagement metrics and playback performance data directly for your index. LlamaIndex takes this raw performance data and embeds it into your vector store, turning ephemeral stats into searchable knowledge. Users query past video performance without hitting the API repeatedly. Your agent searches the indexed analytics to answer questions about which videos drive the most traffic.

Query your media library using LlamaIndex

The `list_videos` tool fetches your entire catalog of video assets to build a semantic index of your media library. This lets your RAG application locate specific video files based on metadata rather than rigid ID matching. The agent pairs this with `get_video_details` to verify processing status before suggesting an asset to a user. You get an intelligent assistant that knows exactly what media is ready to stream.

Manage optimized image sources via MCP Server tools

The `list_image_sources` tool exposes your automatic format conversion and lazy-loading setups directly to LlamaIndex. Your agent indexes these source configurations to troubleshoot loading speeds or verify CDN deployment details. When users ask about image optimization policies, the agent queries this index instead of guessing. You ground every agent response in actual, live configuration data from your organization.

Setup guide

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

Get your connection token →

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

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Gumlet now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Gumlet MCP in LlamaIndex

Use the `llama-index-tools-mcp` package to load the tools into your agent. The agent calls `list_videos` to fetch the metadata and inserts it directly into your vector database.

Yes, by using the `get_video_analytics` tool within a query engine. The agent pulls live statistics during the retrieval step to ground its answers in real-time performance.

It does when you index the output of tools like `list_video_collections`. This lets your agent locate the right folder using natural language queries.

You pass an allowed tools list to the initialization client. This prevents the agent from running destructive actions like `delete_video` while allowing read-only queries.

Your video metadata and folder structures are processed in transit using secure, ephemeral connections. The server never caches your API credentials or CDN configurations, ensuring your media catalog remains private.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript