How to Use the Dailymotion MCP in LangChain

Q: How do I initialize the Dailymotion MCP Server inside a LangChain agent?

Install the adapter using pip install langchain-mcp-adapters langgraph. Use MultiServerMCPClient to connect to the Vinkius endpoint, call client.gettools(), and pass those tools directly to your createagent setup.

Q: Can a LangChain agent automatically handle the multi-step Dailymotion upload process?

Yes, your agent chains getuploadurl and publishvideo sequentially. The agent takes the temporary URL from the first tool, uploads the binary, and then feeds the resulting path into the publishing tool.

Q: How do I trace Dailymotion tool latency in my LangChain runs?

LangSmith automatically logs every call to tools like listvideos or getvideo. You can view the exact execution time, input parameters, and raw JSON outputs returned from Dailymotion inside your LangSmith dashboard.

Control your Dailymotion video library directly from your LangChain reasoning chains using this MCP server.

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Connect Dailymotion MCP to LangChain

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Setup Dailymotion with LangChain

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Chain Dailymotion uploads in LangChain

The `get_upload_url` tool starts your video ingestion chain by getting a temporary target from Dailymotion. Your LangChain agent passes this URL to your storage bucket, pulls the raw video file, and then uses `publish_video` to post it with specific metadata. This multi-step execution runs inside a single LangGraph run. You get exact visibility into how long the file transfer takes and whether the metadata payload matches Dailymotion constraints.

Run Dailymotion playlist updates via MCP Server

The `list_playlists` tool pulls your existing Dailymotion video groups so your agent can inspect current organization. From there, the agent calls `update_video` to sync titles, tags, and channel categories across your library. You can combine this MCP server with other LangChain tools like SQL databases to fetch local video records and update Dailymotion to match. Your agent handles the decision loop, updating only the videos that show metadata mismatches.

Query and analyze content with LangChain and Dailymotion

The `search_videos` tool scans public Dailymotion uploads for target keywords and returns video IDs alongside view counts. Your agent then uses `get_video` to pull deeper metrics like duration and tag structures for high-performing clips. Because LangSmith traces every tool call, you see exactly how many tokens your search queries consume. You can pipeline these metrics into your analytical models to track competitor trends on Dailymotion without manual scraping.

Setup guide

Set up Dailymotion 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 Dailymotion 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({
    "dailymotion-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 Dailymotion 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 Dailymotion. 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 Dailymotion MCP in LangChain

Install the adapter using `pip install langchain-mcp-adapters langgraph`. Use `MultiServerMCPClient` to connect to the Vinkius endpoint, call `client.get_tools()`, and pass those tools directly to your `create_agent` setup.

Yes, your agent chains `get_upload_url` and `publish_video` sequentially. The agent takes the temporary URL from the first tool, uploads the binary, and then feeds the resulting path into the publishing tool.

LangSmith automatically logs every call to tools like `list_videos` or `get_video`. You can view the exact execution time, input parameters, and raw JSON outputs returned from Dailymotion inside your LangSmith dashboard.

The agent catches the error returned by the server, allowing your graph to either retry the call or branch into an error-handling path. You can configure the agent to verify the video status first using `get_video` before attempting the update.

Vinkius hosts the MCP server in a secure, zero-trust V8 Isolate sandbox that isolates your session. Your temporary upload URLs and video metadata are never stored or logged on the platform, keeping your publishing pipeline private.

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