How to Use the Frame.io MCP in LlamaIndex

Q: Can LlamaIndex vector stores hold Frame.io project data?

Yes. You can index the JSON responses from listprojects and listfolders to create a searchable map of your production drives.

Q: Can I search active review links?

Yes. The agent pulls active URLs via listreviewlinks and stores them alongside the project metadata.

Index Frame.io video metadata via the MCP Server into LlamaIndex to query your production assets.

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Connect Frame.io MCP to LlamaIndex

Create your Vinkius account to connect Frame.io 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 Frame.io with LlamaIndex

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Index Video Asset Metadata

The `get_asset_details` and `get_project_details` tools let your LlamaIndex application pull raw metadata into a vector store. You query your entire video catalog based on resolution, frame rate, or creator. Stop guessing which drive holds the 4K b-roll. You just ask. The framework retrieves the exact asset ID and path by searching the indexed API data.

LlamaIndex MCP Server for Feedback

Feed the output of `list_asset_comments` directly into a LlamaIndex document store. Your application answers questions about past creative decisions grounded in actual client feedback. If a director asks why a specific color grade was rejected last month, your RAG setup finds the exact timestamped comment. It stops hallucinations by relying strictly on pulled review notes.

Search Team Directories

Run `list_collaborators` and `list_accounts` to map out who worked on what. LlamaIndex turns this directory structure into queryable context. You find out instantly who approved the final cut. The agent queries the index and returns the specific user profile linked to the project.

Setup guide

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

Install llama-index-tools-mcp and set up a BasicMCPClient to connect the MCP integration. Pass the returned tools to your FunctionAgent.

Yes. You can index the JSON responses from `list_projects` and `list_folders` to create a searchable map of your production drives.

LlamaIndex caches the indexed data locally. You only hit the API when refreshing the index or calling live tools.

Yes. The agent pulls active URLs via `list_review_links` and stores them alongside the project metadata.

The MCP server reads timestamped review notes, frame rates, and collaborator IDs. You control where LlamaIndex stores the resulting vectors. Vinkius relies on a zero-trust architecture, meaning no persistent data remains on our infrastructure.

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