MCP for agents

Build with any agent through the Keystroke MCP server.

The Keystroke MCP server lets you build agents, workflows, triggers, and integrations from any MCP-capable agent — ChatGPT, Claude, Cursor, and more. Connect once, and your agent can create projects, edit code in a hosted workspace, run it, and deploy it, without leaving the chat.

It’s a single hosted Streamable HTTP endpoint:

https://api.keystroke.ai/v1/mcp

This page is about building Keystroke with an MCP client. It’s the reverse of giving your Keystroke agents tools from an external MCP server — for that, see MCP tools.

When to use MCP

Keystroke gives you three ways to build with AI: this MCP server, the CLI with a local project, and the in-app platform agent. We recommend the CLI and a local project whenever your agent can work in an editor on your machine — better tooling, git, tests, and the most mature build loop. When you don’t want to involve your own agent at all, use the platform agent in the web app instead of MCP.

Use this MCP server when a chat-first agent (ChatGPT, Claude, or similar) should build without a local install, or when connecting Keystroke as an MCP tool is the only practical option. Code lives in a hosted workspace instead of your repo; deploys still land on the same platform.

The hosted-workspace MCP path is newer than the CLI. Prefer local development when you can; use MCP when the chat-only or zero-install workflow is worth the tradeoff.

	MCP server (this page)	Local CLI (recommended)
Where you work	A chat-first agent (ChatGPT, Claude, Cursor)	Your own editor (Cursor, Claude Code)
Where code lives	A hosted Keystroke workspace	Your machine
Setup	Connect a URL, sign in once	npm i -g @keystrokehq/cli, scaffold a project
Best for	No local setup; pure chat workflows	Full control of files, git, tests, and editor tooling
Maturity	Newer hosted path	Primary, most stable agent experience

Both build the same projects and deploy to the same platform. Many teams start on the CLI and only add MCP for teammates who build entirely from chat.

Connect a client

Add the Keystroke MCP server to your client, then sign in. Authentication uses OAuth — there’s no API key to paste. The first time your client calls the server, it registers itself and opens a Keystroke login in your browser.

Cursor

Add Keystroke to ~/.cursor/mcp.json (global) or .cursor/mcp.json (per project):

{
  "mcpServers": {
    "keystroke": {
      "type": "http",
      "url": "https://api.keystroke.ai/v1/mcp"
    }
  }
}

Open Cursor Settings → MCP, then click Login next to the Keystroke server to complete the OAuth flow.

Claude

In Settings → Connectors, add a custom connector with the URL:

https://api.keystroke.ai/v1/mcp

Claude opens the Keystroke sign-in to authorize the connection.

ChatGPT

In a Developer mode / connector-capable workspace, add a connector pointing at:

https://api.keystroke.ai/v1/mcp

Authorize it when prompted to complete sign-in.

Other clients

Any MCP client that supports remote (Streamable HTTP) servers with OAuth can connect. Point it at:

https://api.keystroke.ai/v1/mcp

The server advertises its OAuth endpoints automatically, so most clients can self-register with no extra configuration.

Once connected, your agent receives Keystroke’s authoring guidance automatically and can start building.

The build loop

Building over MCP follows the same deploy-first loop as the CLI: create or open a project, edit code in its workspace, run it to check the output, then deploy. Your agent drives this with MCP tools — you just describe what you want.

1. Pick a project

   The agent calls list_organizations and list_projects, or create_project to start fresh. A new project comes with a hosted workspace and the Keystroke CLI ready to go.

2. Build in the workspace

   The agent reads and edits TypeScript under src/ with read_file, write_file, edit_file, list_files, and delete_file — authoring agents, workflows, triggers, and actions just like a local project.

3. Run and inspect

   exec_command runs shell commands in the workspace — including the keystroke CLI, which is authenticated automatically. The agent runs workflows and agents and reads the real output before wiring up dependent steps.

4. Connect integrations

   A workspace can’t open a browser, so when a build needs a connected app, the agent calls connect_app to get a link. You open it to authorize the integration in the web app. See connect and manage apps.

5. Deploy

   Run keystroke deploy through exec_command to build and ship the workspace. The dedicated deploy_project tool is temporarily disabled. See deploy a project.

Tools

The server exposes two groups of tools.

Docs

Always available. These let your agent search and read the Keystroke documentation on demand — the same docs access the CLI exposes, served straight from the MCP server.

Tool	Description
search_docs	Broad or conceptual lookups; returns matching pages and their paths.
query_docs	Exact keyword/regex search and reading pages by path against the docs filesystem.

See docs for agents for how these work.

Projects and workspaces

Tools for building in a hosted workspace. Every tool is scoped to your account and the projects you can access.

Tool	Description
list_organizations	List organizations you belong to.
list_projects	List projects you can access in an organization.
create_project	Create a project and provision its managed repository + shared draft.
read_file	Read a file from the shared unpublished draft.
write_file	Write a file in the shared draft.
edit_file	Apply exact text replacements to a draft file.
list_files	List files in a draft directory.
delete_file	Delete a file or directory in the draft.
exec_command	Run a shell command on a disposable draft checkout.
deploy_project	Temporarily disabled; use exec_command with keystroke deploy.
connect_app	Get a web link to connect an integration to the project.

Next steps

CLI for agents

Build locally in your own editor with the Keystroke CLI.

Docs for agents

How your agent searches and reads the docs while it builds.

Build agents

Author agents, configure models, and add tools.

Deploy a project

How a workspace becomes a running cloud project.