Arize AI MCP Server for VS Code Copilot 10 tools — connect in under 2 minutes
GitHub Copilot in VS Code is the most widely adopted AI coding assistant, embedded directly into the world's most popular code editor. With MCP support in Agent mode, Copilot can access external data and APIs to generate context-aware code grounded in real-time information.
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{
"mcpServers": {
"arize-ai": {
"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 Arize AI MCP Server
Connect your Arize AI observability platform to any AI agent and take full control of your Machine Learning and LLM telemetry workflows through natural conversation.
GitHub Copilot Agent mode brings Arize AI data directly into your VS Code workflow. With a project-scoped config, the entire team shares access to 10 tools. Copilot queries live data, generates typed code, and writes tests from actual API responses, all without leaving the editor.
What you can do
- Model Monitoring & Metrics — List all tracked ML models, extract deep configuration schemas, and fetch real-time metrics (performance, data quality, and prediction drift)
- Evaluation & Alignment — Launch and list automated LLM evaluation runs (e.g., Toxicity, Hallucination, PII filtering) against static datasets and ground truth baselines
- Telemetry Ingestion — Push programmatic raw logs, predictions, and inferences straight into Arize for immediate visualization and tracking
- Space & Environment Management — Browse organizational spaces and segregated deployment environments (Production, Training, Verification)
The Arize AI MCP Server exposes 10 tools through the Vinkius. Connect it to VS Code Copilot 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 Arize AI to VS Code Copilot via MCP
Follow these steps to integrate the Arize AI MCP Server with VS Code Copilot.
Create MCP config
Create a .vscode/mcp.json file in your project root
Add the server config
Paste the JSON configuration above
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
Start using Arize AI
Ask Copilot: "Using Arize AI, help me...". 10 tools available
Why Use VS Code Copilot with the Arize AI MCP Server
GitHub Copilot for Visual Studio Code provides unique advantages when paired with Arize AI through the Model Context Protocol.
VS Code is used by over 70% of developers. adding MCP tools to Copilot means your team can leverage external data without leaving their primary editor
Project-scoped MCP configs (`.vscode/mcp.json`) let you commit server configurations to your repository, ensuring the entire team shares the same tool access
Copilot's Agent mode integrates MCP tools seamlessly with file editing, terminal commands, and workspace search in a single agentic loop
GitHub's enterprise compliance and audit features extend to MCP tool usage, providing visibility into how AI interacts with external services
Arize AI + VS Code Copilot Use Cases
Practical scenarios where VS Code Copilot combined with the Arize AI MCP Server delivers measurable value.
Live API integration: Copilot can query an MCP server, inspect the response schema, and generate typed API client code in the same step
DevSecOps workflows: security teams can give developers access to domain intelligence tools directly in their editor for real-time vulnerability assessment during code review
Data pipeline development: Copilot fetches sample data via MCP and generates transformation scripts, validators, and test fixtures from actual API responses
Documentation generation: Copilot queries available tools and auto-generates README sections, API reference docs, and usage examples
Arize AI MCP Tools for VS Code Copilot (10)
These 10 tools become available when you connect Arize AI to VS Code Copilot via MCP:
get_dataset
Get a specific evaluation dataset
get_metrics
Fetch observability metrics for an ML model
get_model
It defines the inputs, outputs, and features. Get details and metadata for a specific tracked model
ingest_log
payload_json must contain valid Arize payload structures. Ingest raw telemetry logs into Arize
list_datasets
List static evaluation datasets
list_environments
g., Production, Training, Verification) used to segregate model inferences and baseline datasets. List configured environments within Arize
list_evals
g., Toxicity, Hallucination, PII filtering). List automated evaluation runs
list_models
List tracked ML models or LLMs
list_spaces
Spaces separate different models and telemetry datasets. List accessible workspaces within the Arize platform
run_eval
Trigger a custom LLM evaluation run
Example Prompts for Arize AI in VS Code Copilot
Ready-to-use prompts you can give your VS Code Copilot agent to start working with Arize AI immediately.
"List all active Machine Learning models monitored in my workspace."
"Get the evaluation baseline datasets available for our LLM checks."
"Push these 3 mocked prompt responses as telemetry logs to the 'OpenAI-Customer-Service-Bot' model."
Troubleshooting Arize AI MCP Server with VS Code Copilot
Common issues when connecting Arize AI to VS Code Copilot through the Vinkius, and how to resolve them.
MCP tools not available
Arize AI + VS Code Copilot FAQ
Common questions about integrating Arize AI MCP Server with VS Code Copilot.
Which VS Code version supports MCP?
How do I switch to Agent mode?
Can I restrict which MCP tools Copilot can access?
Does MCP work in VS Code Remote or Codespaces?
.vscode/mcp.json work in Remote SSH, WSL, and GitHub Codespaces environments. The MCP connection is established from the remote host, so ensure the server URL is accessible from that environment.Connect Arize AI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Arize AI to VS Code Copilot
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.