Gumlet MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create Collection, Create Video Upload, Delete Video, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Gumlet through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Gumlet app connector for Pydantic AI is a standout in the Image Video category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Gumlet "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Gumlet?"
)
print(result.data)
asyncio.run(main())
* 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
About 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.
Pydantic AI validates every Gumlet tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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
The Gumlet MCP Server exposes 12 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Gumlet tools available for Pydantic AI
When Pydantic AI connects to Gumlet through Vinkius, your AI agent gets direct access to every tool listed below — spanning video-hosting, image-optimization, cdn-delivery, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
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
Connect Gumlet to Pydantic AI via MCP
Follow these steps to wire Gumlet into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Gumlet MCP Server
Pydantic AI provides unique advantages when paired with Gumlet through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Gumlet integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Gumlet connection logic from agent behavior for testable, maintainable code
Gumlet + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Gumlet MCP Server delivers measurable value.
Type-safe data pipelines: query Gumlet with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Gumlet tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Gumlet and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Gumlet responses and write comprehensive agent tests
Example Prompts for Gumlet in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Gumlet immediately.
"Create a new video upload in collection 'col_123' titled 'Annual Report 2026'."
"Check the transcoding status of video 'asset_987'."
"Show me the viewing stats for my latest product video."
Troubleshooting Gumlet MCP Server with Pydantic AI
Common issues when connecting Gumlet to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiGumlet + Pydantic AI FAQ
Common questions about integrating Gumlet MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.