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Connect Alpic to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Control your entire deployment lifecycle programmatically.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 18 capabilities

We ship only the actions that matter.

Capability set01 / 05

01-04

4 capabilities in this set.

Part of 18 available through Alpic.

  1. 01

    Get project analytics

    Retrieve usage data and performance metrics for an MCP project. Use this to monitor health and identify performance trends.

  2. 02

    Get deployment

    Check the status and metadata of a specific MCP deployment. Provide the deployment ID to confirm if the deployment succeeded or review its history.

  3. 03

    Get project

    Fetch detailed information about an existing MCP project. Use this to review current settings before making changes or triggering a deployment.

  4. 04

    Get server info

    Verify the current status and exposed capabilities of an MCP project. This confirms the connector is running correctly and ready for use.

Capability set02 / 05

05-08

4 capabilities in this set.

Part of 18 available through Alpic.

  1. 05

    Get tunnel ticket

    Generate a temporary tunnel URL and ticket token. This lets you test your MCP connector locally before pushing the changes to a live environment.

  2. 06

    List environments

    List all defined environments (dev, staging, prod) for a project. This helps you identify the correct environment IDs needed for deployment or variable management.

  3. 07

    List projects

    Get an overview of all MCP projects in your account. This returns IDs, names, and deployment status, allowing you to manage your entire infrastructure.

  4. 08

    List teams

    List all teams associated with your Alpic account. You must use this first to identify the team under which you want to manage projects.

Capability set03 / 05

09-12

4 capabilities in this set.

Part of 18 available through Alpic.

  1. 09

    List variables

    Audit the environment configuration by listing all variables. The capability returns variable keys and metadata, masking the actual values for security.

  2. 10

    Publish to registry

    Make your MCP connector publicly discoverable by publishing it to the official MCP registry. You provide the project ID and optionally a description.

  3. 11

    Create environment

    Set up a new deployment environment (like dev or staging) for an MCP project. This creates a unique URL for client connections.

  4. 12

    Create project

    This capability establishes a new MCP project within Alpic. You provide the project name and team ID, and it returns the necessary project ID for all subsequent operations.

Capability set04 / 05

13-15

3 capabilities in this set.

Part of 18 available through Alpic.

  1. 13

    Delete project

    Permanently removes an MCP project. This action is irreversible, so use this capability with caution.

  2. 14

    Delete variable

    Removes an unused configuration key from a specific environment. You must provide the project ID, environment ID, and the variable key.

  3. 15

    Deploy environment

    Trigger a new MCP version deployment to a specified environment. This action runs asynchronously, giving you a deployment ID you can use to track the progress.

Capability set05 / 05

16-18

3 capabilities in this set.

Part of 18 available through Alpic.

  1. 16

    Get deployment logs

    Retrieve detailed logs for a specific MCP environment. This is essential for debugging failed deployments or verifying a successful startup.

  2. 17

    Update project

    Modify an existing MCP project's configuration, such as renaming it or pointing it to a new repository branch. You only need to pass the fields you want to change.

  3. 18

    Add variable

    Use this capability to set or update environment variables for an MCP project. You can add critical configuration details like API keys or database URLs to specific environments.

Real work

What teams actually run

01

Debugging a Production Failure

If a live MCP connector fails, ask the AI to fetch the deployment logs and check the current status to pinpoint the exact error.

02

Setting Up a New Feature Branch

Before deploying, use the AI to create a new environment and set the necessary API keys or database URLs for that specific stage.

03

Auditing Credentials

Need to know what variables are active? Ask the AI to list all environment variables for a project to ensure compliance.

04

Preparing for Launch

When a project is stable, the AI can publish it to the MCP registry, making it available for other teams to discover.

Automate a task

Put Alpic to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Alpic works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Alpic to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

972ms average. Fast in production.

Alpic is checked daily against the live service.

Daily averagePeak 1120ms
Oct 3Today
Fastest day
784ms
Slowest day
1120ms
14-day trend
Slowing+21%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 18 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Alpic, so you can see the experience inside your AI.

It does not authenticate your account with Alpic. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Alpic Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_2KgnFzVSaiaSHBNFbROaJ4IhOHTa3rucrY1KgZYb/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Alpic capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "alpic-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_2KgnFzVSaiaSHBNFbROaJ4IhOHTa3rucrY1KgZYb/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Alpic in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Alpic owners hand off.

This MCP is essential for platform teams, DevOps engineers, and AI infrastructure managers. If your job involves managing multiple MCP connectors across different stages, this capability lets your AI client handle the complex, repetitive infrastructure tasks. It eliminates the need for manual dashboard operations.

  • 01

    DevOps Engineer

    Use it to automate continuous deployments, manage environment variables, and debug infrastructure failures.

  • 02

    Platform Team Lead

    Use it to oversee the entire MCP catalog, from listing projects to publishing them to the registry.

  • 03

    AI Infrastructure Manager

    Use it to monitor MCP server health, track latency, and manage deployment variables across multiple environments.

FAQ

Questions Alpic owners ask.

  • 01

    Can I deploy to multiple environments at once?

    Yes. You can create and manage multiple environments (dev, staging, production) for a single MCP project. The capabilities allow you to target specific environments for deployment.

  • 02

    What if my deployment fails? How do I fix it?

    If a deployment fails, you can use the get_deployment_logs capability. This retrieves detailed logs, helping you understand the build output or startup failure point.

  • 03

    Does this MCP handle credentials securely?

    Yes. When managing variables, the capability masks the actual values for security. You can list the keys and metadata using list_variables to audit the configuration.

  • 04

    Is this only for production deployments?

    No. The MCP supports the full lifecycle. You can use get_tunnel_ticket to create development tunnels, allowing local testing before any production push.

  • 05

    Can I deploy environments from specific Git branches directly from the terminal?

    Yes! You can operate create_environment mapping parameters matching your active branches, then instruct your agent to trigger the deploy_environment sync.

  • 06

    Are environment variables secured during deployment processes?

    Absolutely. You can invoke add_variable providing exact tokens without storing them in repositories. They remain encrypted at rest and dynamically injected upon startup.

  • 07

    Can I test server configuration before final production merges?

    Yes. Request your AI agent to trigger get_tunnel_ticket enabling you to natively tunnel local host environments through Alpic before pushing any true integration commits.

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