Model Context Protocol (MCP)

Connect your AI app or editor to Glow over MCP to build, validate, and test automations live. Supported clients include Claude, ChatGPT, Google Gemini, Cursor, VS Code, Zed, Windsurf, Claude Code, Codex CLI, and Gemini CLI.

At a glanceVerified in app · Oct 30, 2026

Use it to: Connect Claude, ChatGPT, Gemini, Cursor, VS Code, or Zed to build, validate, and test automations over MCP
Find it: Your account → MCP (?tab=mcp) and Team settings → MCP (?section=mcp)
Cost: 0 Step credits and 0 Glow AI tokens for building and validating · Step tests use normal rates
Limits: 16 to 26 tools by permission level (Read only, Build drafts, Full access)

Glow also acts as an MCP client: canvas AI Agent Steps can call reviewed external MCP servers.

Connect in 30 Seconds

1. Open Quick Connect

Open Your account → MCP (/app/user/account?tab=mcp) or click Connect AI tool in the Workflow Assistant header (Admin, Manager, or Member role).

2. Pick your AI client

Copy the Server URL (https://api.getglow.ai/mcp) and Workspace ID, or click Add to Cursor / Add to VS Code.

3. Approve permissions and verify

Sign in with Glow and pick Read only, Build drafts (Recommended), or Full access. Call list_workspaces in a new chat (setup commands).

Which Tools Your Client Sees (by Permission Level)

Glow filters tools/list by your connection’s preset in Your account → MCP:

Permission Level / Grant	Tools	Included capabilities
Read only	16 tools	Discovery, schemas, graph reads, `validate_workflow`, run traces (`get_workflow_execution`), and version diffs.
Build drafts (Recommended) or Full access	25 tools	All 16 read tools + 6 draft tools (`create_workflow`, `import_workflow`, `update_workflow`, `delete_workflow_draft`, `save_workflow_version`, `restore_workflow_version`) + 3 test tools (`test_step`, `run_workflow_test`, `cancel_workflow_execution`). Legacy no-test: 22 tools.
Full access + Manage Live automations (Admin)	26 tools	All 25 tools + `set_workflow_status` (publish or pause Live automations).

After editing Your account → MCP → Change permissions, start a new chat to refresh tools/list (troubleshooting).

Why Build & Debug Through Glow MCP

Live Canvas & Schema GroundingBuild Without Copy-Pasting JSON

Queries real app schemas and live picker options (channels, sheets, folders) in batches.
Commits atomic update_workflow batches while your open Glow tab frames changes live.
Discovery, building, and validation cost 0 Glow AI tokens and 0 Step credits.

Validation, Testing & Run TracesDebug Without Switching Tabs

validate_workflow catches missing fields, broken routes, and invalid references before runs.
list_workflow_executions and get_workflow_execution inspect step traces with secrets masked.
test_step and run_workflow_test verify drafts with save_workflow_version checkpoints.

How a Typical MCP Build Loop Works

1. Discover & Wire Draft2. Validate Graph3. Connect Accounts4. Test Steps or Run5. Inspect Trace & Fix

Prompts You Can Try Right Away

Ask in plain English or run a slash command (/build-automation, /debug-failed-run, /explain-automation, /optimize-automation, /test-and-verify-draft):

Build Draft

“Build a draft that receives a webhook lead, classifies it with AI Prompt, gates VIP deals with Human Review, and posts to Slack.” Commits an atomic update_workflow draft and returns connectUrl links.

Debug Failure

“Check why ‘Stripe to NetSuite Sync’ failed today and fix the draft.” Calls list_workflow_executions and get_workflow_execution (secrets masked), patches the Step, and runs validate_workflow.

Test Step

“Test Step 3 on ‘Customer Onboarding’ with sample data from the last run.” Runs test_step on Step 3 alone using its connected account.

Choose Your Task

I Want To	Start Here
Connect ChatGPT, Claude, Gemini, Cursor, VS Code, or Zed	Connecting AI Apps & Editors
Discover components, build drafts, or save checkpoints	MCP Tool Reference
Run a Step or whole-automation test	Testing Automations with MCP
Let a canvas AI Agent call an external MCP server	Glow as an MCP Client
Set workspace budgets and review permissions	MCP Administration

Illustrative sequence, not a live session or API payload. Select a step to explore.

ChatGPT, Claude, Gemini, or IDEPrompt

$User: "Add a Webhook, an AI Triage Step, and a Slack alert for VIP tickets."

Discover tool schemas and component keys, then prepare an update_workflow request.

Streamable HTTP

Illustrative Glow CanvasAwaiting Request

Awaiting edit request...

Architecture & Governance Controls

Building, executing, and administering require separate grants.

1. Atomic Batches

Batch edits save atomically while canvas sync reports separately. Read saved state instead of repeating a committed batch. Use dryRun: true to check edits without saving.

3. Credential Isolation

Bind accounts by ID (accountId or connectionId) rather than placing secrets in prompts or parameters. OAuth tokens and API keys stay in Glow’s encrypted store (account discovery).

4. RBAC & Scoping

Connection grants scope access per client. Step and workflow tests require separate grants and execute real actions (testing prerequisites).

MCP stops only MCP test runs (cancel_workflow_execution); production runs must be stopped in the Glow UI. Calling set_workflow_status requires an Admin connection with Manage Live automations (Manages Live badge). Billable runs share balances under workspace safeguards.

Frequently Asked Questions

Live Safety & Undo

Can an AI client change a Live automation? Only when permitted. Build drafts (Recommended) reads all automations and runs (Live included) while editing and testing drafts only. Under Full access, editing or publishing a Live workflow requires an Admin to enable Manage Live automations in Your account → MCP and pass allowActiveWorkflowMutation: true. Admins can cap workspace permissions in Team settings → MCP, and any connection can be scoped to 100 automations.

Can I undo AI client edits? Yes. Press Cmd+Z / Ctrl+Z, or use save_workflow_version, get_workflow_history, diff_workflow_versions, and restore_workflow_version. Live edits save an automatic checkpoint version first.

Debugging & Billing

Can my AI client debug failed runs? Yes. list_workflow_executions and get_workflow_execution read step traces with secrets masked, then update_workflow and validate_workflow apply and verify the fix.

Does building with MCP use tokens or Step credits? No. Discovery, authoring (create_workflow, update_workflow), history reads, and validation cost 0 tokens and 0 credits. Balance is used only by test_step, run_workflow_test, or generate_workflow.

Server vs. Client

How do Glow MCP Server and Client differ? Glow as an MCP Server lets external AI apps (Claude, ChatGPT, Gemini, Cursor) build and test automations in your workspace. Glow as an MCP Client lets a canvas AI Agent Step call tools on an external HTTPS MCP server under Connections → Agent tools.

Verify it works

Run: Open Your account → MCP (?tab=mcp), connect via Quick Connect, and call list_workspaces
You should see: Your AI client lists your Glow workspace and can inspect or build draft automations.

What’s Next?

👉 Connect your AI app or editor, then build and validate before testing.
Glow as an MCP Client: connect external MCP tools for canvas AI Agents.