Bring Video Hosting
to CrewAI
Learn how to connect Gumlet to CrewAI 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 Gumlet MCP Server?
Connect your Gumlet account to any AI agent and take full control of your video hosting and image optimization workflows through natural conversation.
What you can do
- Video Lifecycle — Manage the complete video lifecycle from creating new uploads and retrieving metadata to monitoring transcoding status
- Media Organization — Create and manage collections/folders programmatically to maintain a structured media library
- Visual Control — Automate thumbnail updates by selecting specific video frames or time offsets for perfect visual representation
- Optimization Insights — Monitor real-time video analytics, viewing metrics, and bandwidth usage for every asset in your account
- Image Source Management — List and manage image optimization sources and organization users to ensure high-fidelity delivery
How it works
1. Subscribe to this server
2. Retrieve your API Key from your Gumlet dashboard (Profile icon > API Key)
3. Start managing your video and image infrastructure from Claude, Cursor, or any MCP client
No more manual status checking or complex asset management through slow web dashboards. Your AI acts as your dedicated media infrastructure engineer.
Who is this for?
- Video Platform Developers — automate asset ingestion and monitor transcoding progress through natural language
- Digital Marketers — retrieve engagement analytics and update video thumbnails across multiple collections
- Content Managers — organize large media libraries and manage team access to specific image sources
Built-in capabilities (12)
Add new folder
Upload new video
Remove video asset
Get profile details
Check video stats
Check video status
List image optimized sources
List team members
List folders
List video assets
Get active webhooks
Set thumbnail offset
Why CrewAI?
When paired with CrewAI, Gumlet becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Gumlet tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Gumlet in CrewAI
Gumlet and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Gumlet to CrewAI 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 Gumlet in CrewAI
The Gumlet 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 CrewAI 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
Gumlet for CrewAI
Every tool call from CrewAI to the Gumlet MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I start a video upload?
Use the create_video_upload tool, which will create the asset in your specified collection and provide a temporary upload_url for your file.
Can I update the thumbnail for a video already uploaded?
Yes! The update_video_thumbnail tool allows you to specify a time offset in seconds. Gumlet will extract that specific frame and set it as the new thumbnail.
Does it support viewing stats and bandwidth usage?
The get_video_analytics tool provides detailed viewing metrics and bandwidth consumption data for any video ID in your account.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.