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Why use Neptune.ai (ML Experiment Tracking) MCP Server with VS Code Copilot?

Bring Mlops
to VS Code Copilot

Create your Vinkius account to connect Neptune.ai (ML Experiment Tracking) to VS Code Copilot and start using all 6 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.

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Get AttributesGet ProjectGet UserList ModelsList ProjectsSearch Runs
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Compatible with every major AI agent and IDE

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Neptune.ai (ML Experiment Tracking)

What is the Neptune.ai (ML Experiment Tracking) MCP Server?

Connect your Neptune.ai account to any AI agent and take full control of your machine learning experimentation, model versioning, and training telemetry through natural conversation.

What you can do

  • Experiment Orchestration — List all managed ML projects and retrieve detailed metadata configurations tracking active runs and workspace boundaries directly from your agent
  • Run Audit & Search — Discover specific training runs or historical experiment state checkpoints mapping deep ML parameter sets and performance bounds securely
  • Attribute Inspection — Extract detailed telemetry capturing the exact variables, accuracy metrics, and loss curves logged during specific execution checkpoints natively
  • Model Registry Management — List and retrieve trained tracking models promoted and logged explicitly, isolating stable versions from ephemeral experimentation runs
  • Organizational Visibility — Enumerate accessible workspaces and projects to understand your ML research footprint and documentation distribution natively
  • Credential Audit — Verify specific user identifies and availability details bound inherently against your active service account token securely
  • Metadata Retrieval — Deep-dive into specific Project or Run IDs to retrieve precise JSON representations and chronological experimentation insights instantly

How it works

  1. Subscribe to this server
  2. Enter your Neptune.ai API Token
  3. Start managing your ML experiments from Claude, Cursor, or any MCP-compatible client

Who is this for?

  • Data Scientists — monitor training progress and verify model metrics through natural conversation without manual dashboard navigation
  • ML Engineers — audit the model registry and verify experiment attributes directly from your workspace terminal
  • AI Researchers — track production model versions and ensure consistent metadata logging across multiple ML projects efficiently

Built-in capabilities (6)

get_attributes

Get parameters mapped within an experiment runtime bounds

get_project

Get specific details for a targeted Neptune ML project

get_user

Get specific user credentials and availability details

list_models

List trained tracking models packaged natively within a project

list_projects

List accessible Neptune workspaces and projects

search_runs

Search explicitly tracked ML experimentation runs inside a project

Why VS Code Copilot?

GitHub Copilot Agent mode brings Neptune.ai (ML Experiment Tracking) data directly into your VS Code workflow. With a project-scoped config, the entire team shares access to 6 tools. Copilot queries live data, generates typed code, and writes tests from actual API responses, all without leaving the editor.

  • 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

See it in action

Neptune.ai (ML Experiment Tracking) in VS Code Copilot

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Enterprise Security

Why run Neptune.ai (ML Experiment Tracking) with Vinkius?

The Neptune.ai (ML Experiment Tracking) connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 6 tools are ready to work instantly without any complex setup.

You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.

Neptune.ai (ML Experiment Tracking)
Fully ManagedNo server setup
Plug & PlayNo coding needed
SecurePrivacy protected
PrivateYour data is safe
Cost ControlBudget limits
Control1-click disconnect
Auto-UpdatesMaintenance free
High SpeedOptimized for AI
Reliable99.9% uptime
Your credentials and connection tokens are fully encrypted

* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure

01 / Catalog

Over 4,000 integrations ready for AI agents

Explore a vast library of pre-built integrations, optimized and ready to deploy.

02 / Credentials

Connect securely in under 30 seconds

Generate tokens to authenticate and link external services in a single step.

03 / Guardian

Complete visibility into every agent action

Audit live requests, latency, success rates, and active security compliance policies.

04 / FinOps

Optimize spending and track token ROI

Analyze real-time token consumption and cost metrics detailed by connection.

Over 4,000 integrations ready for AI agents
Connect securely in under 30 seconds
Complete visibility into every agent action
Optimize spending and track token ROI

Explore our live AI Agents Analytics dashboard to see it all working

This dashboard is included when you connect Neptune.ai (ML Experiment Tracking) using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.

Why Vinkius

Neptune.ai (ML Experiment Tracking) and 4,000+ other AI tools. No hosting, no code, ready to use.

Professionals who connect Neptune.ai (ML Experiment Tracking) to VS Code Copilot through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.

4,000+MCP Integrations
<40msResponse time
100%Fully managed
Raw MCP
Vinkius
Ready-to-use MCPsFind and configure each manually4,000+ MCPs ready to use
Connection SetupManual coding & server setup1-click instant connection
Server HostingYou host it yourself (needs 24/7 uptime)100% hosted & managed by Vinkius
Security & PrivacyStored in plaintext config filesBank-grade encrypted vault
Activity VisibilityBlind execution (no logs or tracking)Live dashboard with real-time logs
Cost ControlRunaway AI token spend riskAutomatic budget limits
Revoking AccessMust delete files or code to stop1-click disconnect button
The Vinkius Advantage

How Vinkius secures Neptune.ai (ML Experiment Tracking) for VS Code Copilot

Every request between VS Code Copilot and Neptune.ai (ML Experiment Tracking) is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.

< 40msCold start
Ed25519Signed audit chain
60%Token savings
FAQ

Frequently asked questions

01

Can I see the accuracy metrics for a specific ML run through my agent?

Yes. Use the get_attributes tool with your Project ID and Run ID. Your agent will retrieve the detailed telemetry logged during that execution, including accuracy, loss, and any custom attributes defined in your code.

02

How do I check which model versions are currently stable in my registry?

The list_models tool retrieves all packaged ML models within a project. Your agent will expose the promoted model versions, helping you distinguish between experimental runs and stable candidates ready for deployment.

03

Can my agent search through hundreds of past ML experimentation runs?

Absolutely. Use the search_runs tool with your Project ID. Your agent will query Neptune's tracking server to identify historical experiment state checkpoints, making it easy to locate specific training results across your entire research timeline.

04

Which VS Code version supports MCP?

MCP support requires VS Code 1.99 or later with the GitHub Copilot extension. Ensure both are updated to the latest version. Older versions of Copilot may not expose the Agent mode toggle.

05

How do I switch to Agent mode?

Open the Copilot Chat panel and look for two mode options: "Ask" and "Agent". Click "Agent" to enable autonomous tool calling. In Ask mode, Copilot provides conversational answers but cannot invoke MCP tools.

06

Can I restrict which MCP tools Copilot can access?

Yes. VS Code shows a tool consent dialog before any MCP tool is invoked for the first time. You can also configure tool access policies at the organization level through GitHub Copilot settings.

07

Does MCP work in VS Code Remote or Codespaces?

Yes. MCP servers configured via .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.

08

MCP tools not available

Ensure you are in Agent mode in Copilot Chat. MCP tools only appear in Agent mode.

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