How to Use the Limelight Networks (Edgio CDN & Streaming API) MCP in LlamaIndex

Q: How does LlamaIndex index metadata from Limelight Networks (Edgio CDN & Streaming API)?

The framework uses the MCP integration to call listassets and getasset. It then converts the returned JSON metadata into document nodes, which are embedded and stored in your vector database for semantic search.

Q: Can I query Limelight Networks (Edgio CDN & Streaming API) CDN logs using LlamaIndex?

Yes. The agent uses listlogs to locate available log files, which can then be parsed and indexed. This lets you ask natural language questions about CDN errors or traffic spikes.

Index live streaming data and CDN performance logs directly into LlamaIndex using our MCP Server to query your video infrastructure.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Limelight Networks (Edgio CDN & Streaming API) MCP to LlamaIndex

Create your Vinkius account to connect Limelight Networks (Edgio CDN & Streaming 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.

GDPR Free for Subscribers

Setup Limelight Networks (Edgio CDN & Streaming API) with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Semantic Search Over Video Metadata

Load your entire video library metadata into a LlamaIndex vector store using `list_assets`. The agent indexes titles, tags, and custom fields so you can query your catalog using natural language instead of rigid database lookups. When you need details on a specific file, the agent calls `get_asset` to retrieve deep metadata and update the index. This ensures your knowledge base stays synchronized with actual CDN state, avoiding stale data and hallucinations.

Grounding QA in Real-Time Playback Reports with MCP Server

Retrieve viewer statistics directly using `get_playback_report` to ground your LlamaIndex analytical queries in actual performance metrics. The agent parses raw views, duration, and completion rates to answer complex questions about audience engagement. This turns raw telemetry into an active knowledge base. Instead of hunting through dashboards, you ask your agent which videos are underperforming, and it checks the latest reports to give you an accurate, data-backed summary.

Linear Channel and Event Auditing

Inspect current configurations of your linear streams for automated compliance auditing with `list_channels`. The agent pulls channel settings via `get_channel` and documents the state of your broadcast network. For live broadcasts, the agent tracks active states using `list_events`. It logs when events start and stop, creating an indexed history of your broadcast operations that you can query or audit at any time.

Setup guide

Set up Limelight Networks (Edgio CDN & Streaming 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 Limelight Networks (Edgio CDN & Streaming 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 Limelight Networks (Edgio CDN & Streaming API) tools.",
)
response = await agent.run("List recent Limelight Networks (Edgio CDN & Streaming API) 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 Edgio. 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 Limelight Networks (Edgio CDN & Streaming API) 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 Limelight Networks (Edgio CDN & Streaming API) MCP in LlamaIndex

The framework uses the MCP integration to call `list_assets` and `get_asset`. It then converts the returned JSON metadata into document nodes, which are embedded and stored in your vector database for semantic search.

Yes. The agent uses `list_logs` to locate available log files, which can then be parsed and indexed. This lets you ask natural language questions about CDN errors or traffic spikes.

You initialize the basic MCP client with the Vinkius endpoint, convert it to a tool spec, and load it into your function agent. The agent then gets direct access to all 17 streaming and CDN tools.

Yes. If the agent identifies missing metadata during an indexing run, it uses `update_asset` to write corrected titles or tags back to the CDN.

This MCP server accesses only CDN metadata, channel configurations, and log listings. All API communication runs through a zero-trust, ephemeral sandbox on Vinkius, ensuring your authentication tokens never leak into the LLM context.

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