H2O.ai MCP Server for Windsurf 6 tools — connect in under 2 minutes
Windsurf brings agentic AI coding to a purpose-built IDE. Connect H2O.ai through Vinkius and Cascade will auto-discover every tool. ask questions, generate code, and act on live data without leaving your editor.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
Vinkius Desktop App
The modern way to manage MCP Servers — no config files, no terminal commands. Install H2O.ai and 2,500+ MCP Servers from a single visual interface.
{
"mcpServers": {
"h2oai": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* 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 H2O.ai MCP Server
Connect your H2O.ai instance to any AI agent and take full control of your machine learning lifecycle, automated data processing, and cluster monitoring through natural conversation.
Windsurf's Cascade agent chains multiple H2O.ai tool calls autonomously. query data, analyze results, and generate code in a single agentic session. Paste Vinkius Edge URL, reload, and all 6 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.
What you can do
- Data Frame Orchestration — List structured datasets securely loaded into H2O clusters and retrieve specific dimensional data mapping explicit frame columns natively
- Model Inventory Auditing — Iterate through tracked machine learning models previously generated inside your cloud instance to verify performance metrics and versions
- Inference Monitoring — Access detailed configuration blocks for active model architectures to verify deployment boundaries and parameters synchronously
- Training Job Oversight — Query timeline nodes tracking long-running tasks and model training jobs queued on the cluster to monitor execution progress
- Cloud Cluster Auditing — Ping root endpoints defining hardware architecture health and memory utilization within your H2O instances flawlessly
- MLOps Command Center — Verify available frames and models to orchestrate complex data science workflows and model evaluations using natural language
- Status Verification — Identify precise executing statuses of ongoing jobs to ensure your AI pipeline is operational and within resource limits securely
The H2O.ai MCP Server exposes 6 tools through the Vinkius. Connect it to Windsurf in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect H2O.ai to Windsurf via MCP
Follow these steps to integrate the H2O.ai MCP Server with Windsurf.
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Add the server
Paste the JSON configuration above into mcp_config.json
Save and reload
Windsurf will detect the new server automatically
Start using H2O.ai
Open Cascade and ask: "Using H2O.ai, help me...". 6 tools available
Why Use Windsurf with the H2O.ai MCP Server
Windsurf provides unique advantages when paired with H2O.ai through the Model Context Protocol.
Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention
Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively
JSON-based configuration means zero code changes: paste a URL, reload, and all 6 tools are immediately available
Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts
H2O.ai + Windsurf Use Cases
Practical scenarios where Windsurf combined with the H2O.ai MCP Server delivers measurable value.
Automated code generation: ask Cascade to fetch data from H2O.ai and generate models, types, or handlers based on real API responses
Live debugging: query H2O.ai tools mid-session to inspect production data while debugging without leaving the editor
Documentation generation: pull schema information from H2O.ai and have Cascade generate comprehensive API docs automatically
Rapid prototyping: combine H2O.ai data with Cascade's code generation to scaffold entire features in minutes
H2O.ai MCP Tools for Windsurf (6)
These 6 tools become available when you connect H2O.ai to Windsurf via MCP:
cloud_status
Get cloud status
get_frame
Get frame
get_model
Get model
list_frames
List frames
list_jobs
List jobs
list_models
List models
Example Prompts for H2O.ai in Windsurf
Ready-to-use prompts you can give your Windsurf agent to start working with H2O.ai immediately.
"List all machine learning models in my H2O cluster"
"What is the current status of the H2O cloud cluster?"
"Show me the last 3 training jobs"
Troubleshooting H2O.ai MCP Server with Windsurf
Common issues when connecting H2O.ai to Windsurf through the Vinkius, and how to resolve them.
Server not connecting
H2O.ai + Windsurf FAQ
Common questions about integrating H2O.ai MCP Server with Windsurf.
How does Windsurf discover MCP tools?
mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.Can Cascade chain multiple MCP tool calls?
Does Windsurf support multiple MCP servers?
mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.Connect H2O.ai with your favorite client
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Connect H2O.ai to Windsurf
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.