Today we’re making it easier to connect your coding agents to Render—and giving them more capabilities once they’re connected.
Our hosted MCP server now supports OAuth, so you can sign in through your browser instead of creating and copying a personal access token. We’ve also added MCP tools for triggering deploys and changing service plans, expanded our library from 3 skills to more than 20, and added full lifecycle management for Render resources to the CLI.
Render is available natively where many coding agents already run, including Cursor, Claude Code, Claude Desktop, Codex, and ChatGPT. Visit render.com/agents to get started.
Why this matters
Coding agents are already good at working inside a repository. They can explain a codebase, implement a feature, and open a pull request. But their work often stops at the edge of the repo because deploying, debugging, querying data, and managing infrastructure require access to the platform running the code.
MCP, the Render CLI, and Render Skills fill in that missing context. Together, they give agents a way to understand your infrastructure, take action on Render, and follow Render-specific best practices.
Connect with OAuth
Previously, connecting an AI tool to Render’s hosted MCP server required creating an API key and adding it to the tool’s configuration. That works, but it adds setup friction and requires you to handle a long-lived credential.
With OAuth, you connect the MCP server, sign in to Render in your browser, and authorize access to your account. That’s it.
API key authentication is still supported. It remains useful for CI jobs, unattended agents, and remote environments where a browser-based sign-in flow doesn’t make sense.
See setup instructions for each supported AI tool.
New MCP tools
We’ve added two more ways for agents to operate your Render services:
- Trigger deploys. Ask your agent to redeploy a service, optionally clearing the build cache. This is useful after changing an environment variable, diagnosing a stale build, or rolling forward a fix.
- Update service plans. An agent can inspect CPU and memory metrics, recommend a different compute plan, and apply the change after you approve it.
These tools build on existing support for creating services and datastores, querying Postgres, and analyzing logs and metrics. Instead of switching between your editor, terminal, and dashboard, you can describe the outcome you want and let your agent assemble the necessary steps.
From 3 Render skills to more than 20
MCP gives an agent access to Render. Skills help it use that access well.
Our expanded skills library covers services, deploys, debugging, monitoring, Postgres, Key Value, and the Render CLI. A supported coding agent can load the relevant guidance when it needs to deploy an application, investigate a failed build, query a database, or choose the right Render resource for a workload.
Install Render for your coding agent, or browse the complete skills library on GitHub.
Full lifecycle management in the CLI
The Render CLI can now manage the full lifecycle of your infrastructure across services, static sites, Postgres, and Key Value. You can create, inspect, update, suspend, resume, query, and delete resources without leaving the terminal.
Every operation supports non-interactive use and structured JSON or YAML output. That makes the same commands useful to a person at the terminal, an agent working on your behalf, or a script running in CI.
For example, you can create managed datastores for a feature branch:
See the CLI command reference for all supported resources and operations.
What this unlocks
Consider a disposable full-stack environment for a pull request. An agent can create a web service, Postgres database, and Key Value instance; deploy the feature branch; run tests against real managed infrastructure; inspect logs and metrics; and remove the environment after the PR merges.
While you can configure this to automatically happen for every PR using Blueprints, an agent can do it too.
A request can be as simple as:
Developer: Create an isolated Render environment for PR #482, run the integration suite, and remove it after merge.
Agent: I’ll provision a web service, Postgres database, and Key Value instance from the PR branch. I’ll return the environment URL, report any test or deployment failures, and ask before deleting resources.
Developer: Go ahead.
Agent: The environment is live and all 126 tests passed. I’ll monitor the PR and remove the three resources after it merges.
The same lifecycle can be scripted with the CLI:
Disposable environments are just one example. These capabilities also support deployment debugging, scheduled data operations, automated recovery, and service-plan changes based on live metrics.
Get started
Visit render.com/agents to install Render for Cursor, Claude Code, Claude Desktop, Codex, or ChatGPT. You’ll get setup instructions for the hosted MCP server and access to Render skills for your tool.
What’s next
We’re continuing to make Render a platform where agents can move beyond writing code and help operate the software they build.
Next, we’re working on granular, scoped access for agents along with policy and guardrails that let you define exactly what an agent is allowed to do.