Bring Ml Observability
to Windsurf
Learn how to connect Arize AI to Windsurf and start using 6 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Arize AI MCP Server?
Connect your Arize AI account to any AI agent and take full control of your machine learning observability and automated model monitoring workflows through natural conversation.
What you can do
- Project & Trace Orchestration — List and monitor active ML tracing projects programmatically, retrieving detailed high-fidelity execution spans and telemetry data in real-time
- Dataset Lifecycle Management — Programmatically create and manage datasets for model evaluation and validation to maintain a perfectly coordinated ML infrastructure
- Experiment Monitoring — Access and track ML experiments to understand high-fidelity model performance, drift, and data quality across different environments
- Model Intelligence Discovery — Retrieve detailed metadata for specific ML models to coordinate your organizational AI strategy directly through your agent
- Operational Monitoring — Access account-level settings and verify API connectivity directly through your agent for instant performance reporting
How it works
1. Subscribe to this server
2. Retrieve your API Key from your Arize dashboard (Settings > API)
3. Start orchestrating your ML observability pipeline from Claude, Cursor, or any MCP client
No more manual logging into observability portals to check model drift or trace spans. Your AI acts as your dedicated ML engineer and observability coordinator.
Who is this for?
- ML Engineers — instantly retrieve span details and analyze model traces using natural language commands
- Data Scientists — monitor experiment results and manage datasets for validation without leaving your creative workspace
- AI Developers — automate the oversight of LLM and ML model health through simple AI queries
Built-in capabilities (6)
Create a dataset
Get model details
List datasets
List experiments
List projects
List spans
Why Windsurf?
Windsurf's Cascade agent chains multiple Arize 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.
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Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention
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Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively
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JSON-based configuration means zero code changes: paste a URL, reload, and all 6 tools are immediately available
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Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts
Arize AI in Windsurf
Arize AI and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Arize AI to Windsurf 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 Arize AI in Windsurf
The Arize AI 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 6 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Windsurf 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
Arize AI for Windsurf
Every tool call from Windsurf to the Arize AI 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 find my Arize API Key?
Log in to your account, navigate to Settings > API, and generate or copy your unique secret key.
Can I track model drift via AI?
Yes! Use the list_experiments tool to retrieve data on active model evaluations and track performance variations programmatically.
How do I retrieve telemetry traces?
Use the list_spans tool to retrieve high-fidelity execution spans and traces for your ML projects directly from the platform.
How does Windsurf discover MCP tools?
Windsurf reads the 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?
Yes. Cascade is an agentic system. it can plan and execute multi-step workflows, calling several tools in sequence to accomplish complex tasks without manual prompting between steps.
Does Windsurf support multiple MCP servers?
Yes. Add as many servers as needed in mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.
Server not connecting
Check Settings → MCP for the server status. Try toggling it off and on.
