How to Use the D-ID MCP in LlamaIndex

Q: Does LlamaIndex support custom presenter images for D-ID?

Absolutely. Your agent can take a face image file, run uploadimage to get a public URL, and then pass that URL to createtalk to generate a custom avatar video.

Q: How do I check if a video is finished rendering?

You use gettalk or getclip to check the current status of your render. These tools return status strings like done along with the final MP4 URL once the video generation process completes.

Index D-ID video metadata and generate talking avatars directly from your LlamaIndex RAG workflows.

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Connect D-ID MCP to LlamaIndex

Create your Vinkius account to connect D-ID 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 D-ID with LlamaIndex

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Index video metadata with the D-ID MCP Server

Index your video metadata using `list_talks` directly into your LlamaIndex knowledge base. Ground your video production in real data by indexing your entire video library. This MCP Server lets your LlamaIndex agent fetch metadata and ingest the results directly into your vector store for semantic search. Instead of guessing what videos you already created, your agent can query past projects. It retrieves details about presenters, creation dates, and statuses, ensuring your RAG system knows exactly what video assets are available before creating duplicates.

Generate talking avatars from retrieved documents

Generate interactive video responses using `create_talk` or `create_clip` based on retrieved documents. Turn static search results into interactive video responses. Your RAG pipeline can connect to this MCP Server to retrieve text from your document index and pass it directly to the video generation tools. You can also use `create_talk_audio` if your index contains audio files or voice clips. The agent matches the retrieved audio with a presenter selected via `list_presenters` to output a fully synced video response.

Clean up video assets and check credit balances

Purge old assets and check your remaining balance using `delete_talk` and `get_credits`. Keep your external storage and video lists organized automatically. Your agent can run the deletion tool on old or unused video generations, ensuring your indexed video library stays clean and free of redundant files. Before triggering expensive video generation pipelines, the agent can check your D-ID plan limits. This lets your LlamaIndex application gracefully handle low-credit scenarios without throwing unexpected runtime errors.

Setup guide

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

Honestly, LlamaIndex can ingest the video metadata. Your agent calls `list_talks` or `get_talk` to retrieve the video URLs and creation details, then indexes this metadata into your vector store so you can search past runs semantically.

You register the server's tools with your LlamaIndex FunctionAgent. When a user submits a query that requires video output, the agent automatically decides to call `create_talk` or `create_clip` to generate the video response.

Absolutely. Your agent can take a face image file, run `upload_image` to get a public URL, and then pass that URL to `create_talk` to generate a custom avatar video.

You use `get_talk` or `get_clip` to check the current status of your render. These tools return status strings like done along with the final MP4 URL once the video generation process completes.

Vinkius hosts this MCP Server in a secure, ephemeral sandbox environment. Your D-ID API credentials, uploaded presenter images, and voice audio files are processed in real-time and never cached on our servers, keeping your media assets safe from exposure.

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