Bring Video Intelligence
to LangChain
Learn how to connect Tubular to LangChain and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Tubular MCP Server?
Connect your Tubular Labs video intelligence account to any AI agent and simplify how you analyze digital video trends, creator performance, and cross-platform audience metrics through natural conversation.
What you can do
- Video Insights — Retrieve detailed performance metrics and trending data for individual videos or categories across social platforms.
- Creator Intelligence — Search for creators and fetch high-level performance summaries, trends, and audience ratings.
- Audience Demographics — Analyze audience breakdowns (age, gender, location) for specific videos or creators to refine your targeting.
- Sponsorship Tracking — List brand sponsors and monitor sponsored video campaigns to understand the competitive landscape.
- Audience Overlap — Analyze shared audience between two creators or content properties to identify partnership opportunities.
- Operational Monitoring — Check API health and rate limits to ensure your intelligence engine is always running.
How it works
1. Subscribe to this server
2. Enter your Tubular API Key (found in your developer settings)
3. Start analyzing the video ecosystem from Claude, Cursor, or any MCP client
Who is this for?
- Media Agencies & Brands — quickly identify high-performing creators and analyze sponsored content trends via simple AI commands.
- Content Strategists — monitor video trends and cross-platform audience demographics directly from the workspace.
- Data Analysts — retrieve granular video metrics and creator audience ratings via the AI assistant.
Built-in capabilities (12)
Check API health status
Get current API rate limits
Analyze shared audience between entities
Get reach and engagement ratings
Get summary for a specific creator
Get trends for a specific creator
) for a specific video. Get audience demographics for a video
Get insights for a specific video
List trending videos
List sponsored video campaigns
List sponsors and brand partners
g., name or keywords). Search for creators
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Tubular through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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The largest ecosystem of integrations, chains, and agents. combine Tubular MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Tubular queries for multi-turn workflows
Tubular in LangChain
Tubular and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Tubular to LangChain through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Tubular in LangChain
The Tubular MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LangChain only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Tubular for LangChain
Every tool call from LangChain to the Tubular MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I see the audience demographics for a specific YouTube video?
Yes! Use the get_video_demographics tool and provide the Video ID. Your agent will retrieve the age and gender breakdowns for that specific piece of content.
How do I analyze the shared audience between two different creators?
Use the get_audience_overlap tool and provide the IDs for both entities. The agent will return the percentage and metrics of the audience that both creators share.
Is it possible to see which brands are sponsoring a specific creator?
Absolutely. Run the list_sponsored_campaigns query or search for sponsors using the list_sponsors tool to retrieve data on brand partnerships within the video ecosystem.
How does LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
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Install: pip install langchain-mcp-adapters