How to Use the D-ID MCP in LangChain

Q: How do I pass D-ID video outputs to other LangChain tools?

Here's the thing: you can feed the output URL from gettalk or getclip directly to subsequent nodes in your LangChain graph. Since the tools return standard JSON payloads, your agent reads the video link and can immediately pass it to email tools, Slack, or database steps in the same chain.

Q: Can I use custom audio files for D-ID avatars within LangChain?

Yes, you can. Your LangChain agent can call createtalkaudio by passing a URL to a pre-recorded audio file. The server handles the lip-sync setup automatically, making it easy to pair voice generation tools with video creation.

Q: How does LangChain monitor the progress of a D-ID video build?

Your agent can run a polling loop using gettalk or getclip to check the generation status. These tools return status fields like created, started, or done, letting your chain wait until the final video URL is ready before moving to the next step.

Q: Is it possible to use custom faces instead of stock presenters?

Definitely. You use uploadimage to send a face photo to the MCP Server, which returns an image URL. Your agent then passes that URL directly into createtalk to generate a custom talking avatar.

Build LangChain pipelines that generate talking avatar videos and clips directly from your agentic workflows.

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Connect D-ID MCP to LangChain

Create your Vinkius account to connect D-ID to LangChain 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 LangChain

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Claude

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Automate video generation in LangChain chains

Generate videos directly from your LangChain agents using `list_presenters` and other video tools. This MCP Server lets your agent decide when a video is needed, pick a presenter, and trigger the generation automatically. You don't have to write custom API wrappers or manage HTTP requests manually inside your chain. The output of one step flows right into the next. Your agent can upload a custom headshot using `upload_image` and then immediately use that image to generate a talking head video using `create_talk`. All of this happens within a single, unified run, tracked end-to-end via LangSmith.

Generate custom talking heads from text or audio

Create talking avatar videos from text or audio using `create_talk` or `create_talk_audio`. Give your digital avatars a voice by feeding text or pre-recorded audio directly to the API. Your agent can select a stock presenter or upload custom assets, then trigger the lip-sync process automatically. If you want to move fast without managing custom images, call `create_clip` to build a video using D-ID's built-in stock presenters. You can monitor the video build status in real-time with `get_talk` or `get_clip` before passing the final MP4 URL to the next node in your graph.

Manage video assets and track credit usage

Track your video project library and manage credits using `list_talks` and `get_credits`. Keep your production pipeline clean by letting your agents handle storage and budget limits. The D-ID MCP Server lets your agent fetch a list of past video projects and clean up old or failed generations using `delete_talk` to keep your workspace organized. Running out of credits mid-run ruins automated workflows. To prevent this, your agent can run the credit check before initiating a heavy video generation batch, letting you pause or alert your team if resources run low.

Setup guide

Set up D-ID MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes D-ID tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "d-id-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent D-ID transactions"
    })
    print(result["messages"][-1].content)

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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 LangChain

Here's the thing: you can feed the output URL from `get_talk` or `get_clip` directly to subsequent nodes in your LangChain graph. Since the tools return standard JSON payloads, your agent reads the video link and can immediately pass it to email tools, Slack, or database steps in the same chain.

Yes, you can. Your LangChain agent can call `create_talk_audio` by passing a URL to a pre-recorded audio file. The server handles the lip-sync setup automatically, making it easy to pair voice generation tools with video creation.

Your agent can run a polling loop using `get_talk` or `get_clip` to check the generation status. These tools return status fields like created, started, or done, letting your chain wait until the final video URL is ready before moving to the next step.

Definitely. You use `upload_image` to send a face photo to the MCP Server, which returns an image URL. Your agent then passes that URL directly into `create_talk` to generate a custom talking avatar.

Vinkius runs this MCP Server in an isolated, zero-trust sandbox where your D-ID API keys and uploaded face images are never stored. Audio files and generated video links are processed ephemerally, ensuring your media assets remain private and are only accessible by your running LangChain agent.

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