Deplomo
Sign in

AI coding assistants: connect your agent to Deplomo

Connect supported AI coding assistants, including Claude Code, Cursor, and Codex, to Deplomo with one command. Explore the available service-management tools; service creation and deployment are currently paused.

Choose your agentMCP connection guide

Give this prompt to your agent (Claude Code, Cursor, Codex or another supported client):

Set me up on Deplomo: https://deplomo.com/agent-ready.md
Claude

Inspect this project and tell me what it would need before deployment.

Company website project

Connect in three steps

Set it up once to use it across projects on this device.

Install and sign in

Install the Deplomo CLI and sign in with deplomo login.

Connect an agent

The install command adds the MCP connector and Deplomo guide to your project.

Describe the outcome you want

Tell the agent what you want to do. It chooses the tools and checks the result.

Choose the tool you code with

Each tool page shows the setup command and config file path, plus example prompts to get started.

Codex

OpenAI agent

Connect Codex to Deplomo MCP tools to inspect existing service status and logs, where available. Service creation and deployment are currently paused.

.codex/config.toml

Claude Code

Anthropic agent

Connect Claude Code to Deplomo MCP tools to inspect available information about existing services. Service creation and deployment are currently paused.

.mcp.json

Cursor

Smart code editor

Connects Cursor's built-in agent to live project and service data from Deplomo, so its answers reflect the actual state of your infrastructure.

.cursor/mcp.json

Gemini Antigravity

Google agent

Connects to Deplomo resources through MCP to perform cloud tasks from within Antigravity.

.agents/mcp_config.json

GitHub Copilot

Agent mode in VS Code

Connects Copilot agent mode to Deplomo through VS Code's MCP configuration file.

.vscode/mcp.json

OpenCode

Open-source agent

Enables Deplomo as a local MCP server in OpenCode. The choice of model is still up to you.

opencode.json

Devin

Software development agent

Connect Devin to Deplomo MCP tools to inspect available service information and diagnostics. Service creation and deployment are currently paused.

.devin/mcp_config.json

Pi

Command-line agent

Provides a local connection for working with Deplomo resources from within a command line workflow.

.pi/mcp.json

Grok

xAI agent

Uses the shared MCP template to view project status and perform authorized operations on Deplomo services.

.mcp.json

Compare AI coding assistants and software development agents

The table compares example tools by environment, workflow, and MCP support. Model names are illustrative; availability and context limits depend on the selected model and provider.

AI assistantEnvironmentExample modelsTypical featuresSetup guide
Claude CodeTerminal CLIClaude 3.7 / 3.5 SonnetTerminal-based coding assistance for tasks such as code analysis and debuggingClaude Code
CursorCode editor based on VS CodeExamples include Claude Sonnet and GPT-4o; availability varies by plan and providerAI-assisted editing across files, code chat, and frontend coding supportCursor
OpenAI Codex / CLITerminal and shell assistantExamples include the o-series and GPT-4o; availability varies by plan and providerHelp with system scripts and Linux command troubleshootingCodex
Gemini AntigravityGoogle’s agent-focused development environmentGemini 2.0 Pro / FlashMulti-agent workflows and architecture review; context limits depend on the selected model and providerGemini Antigravity
GitHub CopilotVS Code and JetBrains extensionsExamples include GPT-4o and Claude; availability varies by plan and providerCode completion and coding assistance in the editorGitHub Copilot
Devin AIAI software engineering agentCognition models and toolsCan assist with issue triage, tests, pull requests, and end-to-end testing, depending on setupdevin ai
OpenCodeOpen-source terminal environmentLocal models such as Ollama or cloud APIsModel choice and customization; data handling depends on the selected model and providerOpenCode
Pi Coding AgentLightweight terminal coding agentOptimized coding models, depending on configurationCan process commands, inspect logs, and assist with routine tasks, subject to permissionspi coding agent
Grok (xAI)Analysis and problem-solving agentGrok 2 / Grok 3Can help analyze complex log patterns and longer software context; results depend on model and inputGrok setup

A guide to choosing an AI coding assistant and connecting it to cloud tools

AI coding tools have changed how many software teams work. Coding assistants can help explore a repository, run tests, and work with infrastructure tools when configured and authorized. What an agent can do depends on its model, connected tools, and permissions. Service creation and deployment through Deplomo are currently paused.

The Model Context Protocol (MCP) for connecting AI agents to cloud tools

MCP provides a standard way to connect compatible agents to external tools. After configuring an agent, you can use the Deplomo tools available to that client and account, subject to permissions. These tools can provide information such as service status, logs, metrics, or domains; do not share secret values. Service creation and deployment are currently paused.

MCP tools for PaaS services

With an MCP client configured, you can ask about available information for a Deplomo service without switching to the web dashboard. The tools can provide details such as service status, build or runtime logs, and metrics, depending on access. PaaS service Service creation and deployment are currently paused. Review any changes suggested by your coding assistant before applying them.

Choosing an AI coding assistant for your project

The right tool depends on your workflow and the features available in your chosen model and plan:

  • If you spend most of your time in an editor, tools such as Cursor and GitHub Copilot offer editor-based coding assistance. Features and responsiveness depend on your setup.
  • For terminal-based work, Claude Code and OpenAI Codex provide command-line workflows; their capabilities depend on the model, configuration, and permissions.
  • For multi-step tasks and codebase review, tools such as Devin and Gemini Antigravity offer agent-based workflows. Results depend on the task and configuration.

Data handling when connecting agents to cloud tools

When an agent is connected through MCP, it can use the tools available to that client and account, subject to permissions. Review each requested action and avoid sharing secret values in prompts. Available operations vary; service creation and deployment through Deplomo are currently paused.

The agent sees the current service state

MCP connects your agent to Deplomo. The agent uses it to read account information and work in the specified project and environment. The installed Deplomo guide explains the checks and tool limits.

Project and service

The agent finds the right project and applies changes to the intended service.

Deploy code

The agent deploys the current folder and waits for the build result.

Logs and usage metrics

The agent compares build and runtime logs with real metrics to diagnose errors.

Domains and access

The agent connects your domain to the service and shows the DNS records you need.

Environment variables

The agent identifies required variables. It sets secret values only with your approval.

Usage and costs

The agent reads usage and billing information directly from your Deplomo account.

Try it on a real project

“Deploy this project to Deplomo. If the build fails, read the logs, diagnose the cause and tell me before changing any settings.”

Create a Deplomo accountRead the connection guide