_Manage your deployments using natural language with Claude Code, OpenAI Codex, Gemini CLI, and any MCP-compatible AI assistant._

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The way developers interact with their tools is changing. Instead of switching between dashboards, terminals, and documentation, what if you could simply ask your AI assistant to check a deployment status, debug a failed release, or push the latest changes to production?

Today, we're excited to announce the **DeployHQ MCP Server** — a new integration that brings the power of natural language to your deployment workflow. Whether you're using Claude Code, OpenAI Codex, Google's Gemini CLI, or any other MCP-compatible assistant, you can now manage your [DeployHQ](https://www.deployhq.com) deployments without ever leaving your coding environment.

## What is MCP?

The **Model Context Protocol (MCP)** is an open standard that allows AI assistants to interact with external tools and services in a structured, secure way. Think of it as a universal adapter that lets AI models understand and use your favourite developer tools.

Instead of copying and pasting between your AI assistant and various dashboards, MCP creates a direct bridge. Your AI can discover available tools, understand their parameters, and execute actions on your behalf — all through natural conversation.

## What Can You Do With the DeployHQ MCP Server?

The [DeployHQ](https://www.deployhq.com) MCP Server exposes seven powerful tools that cover your entire deployment workflow:

1. **List Projects** — View all projects in your [DeployHQ](https://www.deployhq.com) account with their repository information and deployment status
2. **Get Project Details** — Dive deep into a specific project's configuration
3. **List Servers** — See all servers configured for any project
4. **List Deployments** — Browse deployment history with pagination support
5. **Get Deployment Details** — Examine specific deployment information
6. **Get Deployment Log** — Retrieve complete logs for debugging failed deployments
7. **Create Deployment** — Queue new deployments with full control over options like branch, build commands, and caching

## Real-World Use Cases

### Debugging a Failed Deployment

Instead of clicking through the dashboard to find logs, simply ask:

> "Why did the last deployment fail for my-website?"

Your AI assistant will automatically find the failed deployment, retrieve the logs, and analyse what went wrong — often suggesting fixes before you even ask.

### Quick Status Checks

During a busy day of shipping features, stay informed without context switching:

> "What's the status of my latest deployment for api-backend?"

### Deploying with Confidence

When you're ready to ship:

> "Deploy the latest changes to production for my-website"

Your AI assistant will find the project, identify the production server, determine the correct revisions, and queue the deployment — then report back with the status.

### Monitoring Multiple Projects

For agencies or teams managing multiple sites:

> "List all my [DeployHQ](https://www.deployhq.com) projects and show which ones have pending deployments"

## Setting Up with Claude Code

Claude Code is Anthropic's command-line tool for agentic coding that runs directly in your terminal. Here's how to connect it to DeployHQ:

1. Ensure you have Node.js 18 or higher installed
2. Get your [DeployHQ](https://www.deployhq.com) credentials: your login email, API key (found in Settings → Security), and account name from your [DeployHQ](https://www.deployhq.com) URL
3. Add the following to your `.claude.json` file in your project directory:

```
{
  "mcpServers": {
    "deployhq": {
      "command": "npx",
      "args": ["-y", "deployhq-mcp-server"],
      "env": {
        "DEPLOYHQ_EMAIL": "your-email@example.com",
        "DEPLOYHQ_API_KEY": "your-api-key",
        "DEPLOYHQ_ACCOUNT": "your-account-name"
      }
    }
  }
}
```

Now you can ask Claude Code to manage your deployments while you're coding. Spotted a bug in production? Ask Claude to check the deployment logs. Ready to ship a fix? Ask it to deploy — all without leaving your terminal.

## Setting Up with OpenAI Codex

OpenAI's Codex CLI is a lightweight coding agent that runs locally in your terminal, and it has full support for MCP servers. To connect DeployHQ:

1. Install Codex CLI if you haven't already: `npm i -g @openai/codex`
2. Add the MCP server using the Codex CLI command:

```
codex mcp add deployhq \
  --env DEPLOYHQ_EMAIL=your-email@example.com \
  --env DEPLOYHQ_API_KEY=your-api-key \
  --env DEPLOYHQ_ACCOUNT=your-account-name \
  -- npx -y deployhq-mcp-server
```

Alternatively, you can manually edit your `~/.codex/config.toml`:

```
[mcp_servers.deployhq]
command = "npx"
args = ["-y", "deployhq-mcp-server"]

[mcp_servers.deployhq.env]
DEPLOYHQ_EMAIL = "your-email@example.com"
DEPLOYHQ_API_KEY = "your-api-key"
DEPLOYHQ_ACCOUNT = "your-account-name"
```

Once configured, launch Codex and use `/mcp` to verify your [DeployHQ](https://www.deployhq.com) server is connected. Then simply ask Codex to manage your deployments as part of your coding workflow.

## Setting Up with Gemini CLI

Google's Gemini CLI is an open-source AI agent that brings Gemini directly into your terminal, with built-in MCP support. Here's how to connect DeployHQ:

1. Install Gemini CLI: `npm install -g @google/gemini-cli`
2. Configure the MCP server in `~/.gemini/settings.json`:

```
{
  "mcpServers": {
    "deployhq": {
      "command": "npx",
      "args": ["-y", "deployhq-mcp-server"],
      "env": {
        "DEPLOYHQ_EMAIL": "your-email@example.com",
        "DEPLOYHQ_API_KEY": "your-api-key",
        "DEPLOYHQ_ACCOUNT": "your-account-name"
      }
    }
  }
}
```

Launch Gemini CLI and use `/mcp` to verify the connection. You can then interact with [DeployHQ](https://www.deployhq.com) using natural language, leveraging Gemini 2.5 Pro's powerful reasoning capabilities to debug deployments, analyse logs, and manage your infrastructure.

## Security First

We've designed the [DeployHQ](https://www.deployhq.com) MCP Server with security as a priority:

- **Local execution** — The server runs on your machine; credentials never leave your environment
- **Environment variables** — Credentials are passed securely and never written to disk
- **HTTPS only** — All API communication uses encrypted connections
- **No telemetry** — We don't collect any usage data or analytics

Your API key has the same permissions as your [DeployHQ](https://www.deployhq.com) user account, so you maintain full control over what the AI assistant can access.

## Managing Multiple Accounts

Working with multiple [DeployHQ](https://www.deployhq.com) accounts? Perhaps separate staging and production environments? Simply configure multiple servers:

```
{
  "mcpServers": {
    "deployhq-production": {
      "command": "npx",
      "args": ["-y", "deployhq-mcp-server"],
      "env": {
        "DEPLOYHQ_EMAIL": "prod@example.com",
        "DEPLOYHQ_API_KEY": "prod-api-key",
        "DEPLOYHQ_ACCOUNT": "production-account"
      }
    },
    "deployhq-staging": {
      "command": "npx",
      "args": ["-y", "deployhq-mcp-server"],
      "env": {
        "DEPLOYHQ_EMAIL": "staging@example.com",
        "DEPLOYHQ_API_KEY": "staging-api-key",
        "DEPLOYHQ_ACCOUNT": "staging-account"
      }
    }
  }
}
```

## Getting Started

Ready to bring AI-powered deployment management to your workflow?

1. **Get your credentials** — Find your API key in [DeployHQ](https://www.deployhq.com) under Settings → Security
2. **Choose your AI assistant** — Claude Code, Codex CLI, Gemini CLI, or any MCP-compatible tool
3. **Configure the server** — Follow the setup instructions above
4. **Start deploying** — Ask your assistant to list your projects and go from there

The [DeployHQ](https://www.deployhq.com) MCP Server is available now via npx, so there's nothing to install permanently — it downloads and runs the latest version automatically.

For detailed documentation, troubleshooting guides, and the full API reference, visit our [MCP Server support page](https://www.deployhq.com/support/mcp-server).

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## Resources

- [DeployHQ MCP Server Feature Page](https://deployhq.com/features/deployhq-mcp)
- [npm Package](https://www.npmjs.com/package/deployhq-mcp-server)
- [GitHub Repository](https://github.com/deployhq/deployhq-mcp-server)
- [Model Context Protocol Specification](https://modelcontextprotocol.io/)

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_The future of deployment management is conversational. Try the [DeployHQ](https://www.deployhq.com) MCP Server today and experience the difference._