Render Mcp logo

Render Mcp

Organization
render-oss
render-mcp

Connects and configures the Render MCP server for AI coding tools—setup per tool (Cursor, Claude Code, Codex), authentication, workspace selection, capability discovery, and troubleshooting. Use when MCP is not configured, list_services() fails, the user asks about Render MCP setup, or an action skill needs MCP but it's not connected yet. Trigger terms: MCP, Render MCP, list_services, MCP setup, MCP server, OAuth, API key, Bearer token, mcp.render.com, workspace selection.

Overview

Publisherrender-oss
Repositoryskills
Skill namerender-mcp
Stars
90
Forks
21
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by render-oss on GitHub. Read the source before you install it.

Installation

Install the Render Mcp AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/render-oss/skills/tree/main/skills/render-mcp
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/render-oss/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/render-mcp .claude/skills/render-mcp
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Render Mcp in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Render Mcp on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Render Mcp is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Render MCP Server

The Render MCP server lets AI coding tools manage Render resources directly. This skill covers setup, authentication, workspace selection, capability discovery, and troubleshooting.

Action skills (render-deploy, render-debug, render-monitor) use MCP tools for their workflows. If MCP is not connected, set it up using this skill first.

Before configuring, troubleshooting, or using Render MCP, read references/render-access.md for the current server, authentication, workspace, capability-discovery, and fallback workflow.

When to Use

  • list_services() fails or MCP tools are unavailable
  • First-time Render MCP setup for any AI tool
  • User asks how to connect their AI tool to Render
  • Switching workspaces or troubleshooting auth errors
  • Discovering which MCP tools exist and what they do

Current Setup and Capabilities

Follow references/render-access.md to fetch the current MCP documentation, configure the client, verify read-only access, select the intended workspace, and inspect the tools actually available. Do not rely on a memorized tool catalog.

If the user has not identified their AI tool, ask which tool they use before giving client-specific setup instructions. Prefer the official Render plugin or connector and its browser-based OAuth flow when available. For a manual API-key setup, create a key at https://dashboard.render.com/u/settings#api-keys and use the hosted endpoint https://mcp.render.com/mcp.

Manual client setup

For Cursor, add this configuration to ~/.cursor/mcp.json, restart Cursor, and verify the connection with list_services():

json
{
  "mcpServers": {
    "render": {
      "url": "https://mcp.render.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_API_KEY>"
      }
    }
  }
}

For Claude Code, add the server with:

bash
claude mcp add --transport http render https://mcp.render.com/mcp --header "Authorization: Bearer <YOUR_API_KEY>"

Restart Claude Code and verify with list_services(). To replace a stale manual configuration, run claude mcp remove render before adding it again.

For Codex, follow the current OAuth or API-key configuration fetched through references/render-access.md. If the configuration obtains its bearer token from RENDER_API_KEY, that variable must be available in the environment where Codex starts; restart Codex after changing it.

Empty results and workspace selection

MCP operations run against the active workspace. If list_services() connects successfully but returns no services, first call get_selected_workspace(), then list_workspaces() if the wrong workspace might be selected. Also verify that the credential or RENDER_API_KEY belongs to an account with access to the intended workspace. Do not diagnose the server URL as the primary problem when the MCP call itself succeeds.

Troubleshooting

See references/troubleshooting.md for connection errors, auth failures, timeout issues, and tool-specific quirks.

References

DocumentContents
references/render-access.mdCurrent MCP and CLI access, authentication, workspace, capability-discovery, and authorization workflow
references/troubleshooting.mdConnection errors, auth failures, tool-specific issues, timeout handling

Related Skills

  • render-deploy — Deploy flows using MCP tools
  • render-debug — Debug failures using MCP logs and metrics
  • render-monitor — Monitor health using MCP metrics
  • render-cli — CLI alternative when MCP is unavailable

Current documentation retrieval

Whenever this skill directs you to consult current Render documentation:

  1. Retrieve the linked Markdown document directly with an available URL-fetching tool or HTTP client, such as curl. Do not substitute web-search summaries for the document.
  2. Confirm that retrieval succeeded and returned the expected document, then read its contents. Saving a file or printing its path is not sufficient.
  3. If the request fails or your tool cannot read the Markdown response, open and read the linked HTML version instead.
  4. If neither version can be retrieved, disclose that the current reference is unavailable and follow any topic-specific fallback in the skill. Use bundled guidance only for stable constraints, and do not guess at changeable platform details.

When a task requires multiple references, apply this workflow to each one and distinguish the documents you verified from those that remain unavailable.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Render Mcp AI skill do?

Connects and configures the Render MCP server for AI coding tools—setup per tool (Cursor, Claude Code, Codex), authentication, workspace selection, capability discovery, and troubleshooting. Use when MCP is not configured, list_services() fails, the user asks about Render MCP setup, or an action skill needs MCP but it's not connected yet. Trigger terms: MCP, Render MCP, list_services, MCP setup, MCP server, OAuth, API key, Bearer token, mcp.render.com, workspace selection.

Why use Render Mcp on TypingMind?

Because you install it once and use it with any model. Render Mcp is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Render Mcp in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/render-oss/skills/tree/main/skills/render-mcp. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Render Mcp?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Render Mcp?

As many as you like. As long as a model supports skills, you can use Render Mcp with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Render Mcp AI skill free?

Yes. It is published on GitHub by render-oss under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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