MCP server - Layer

Layer provides an MCP (Model Context Protocol) server that lets you generate images, 3D assets, video, and audio directly from AI conversations — no code required.

Connect to Layer

OAuth
API Key

Connect using your Layer account — recommended for most agents.

Open Settings > Developer > MCP Servers.

Add this config:

{
  "mcpServers": {
    "Layer": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.app.layer.ai/mcp"
      ]
    }
  }
}

Requires Node.js. mcp-remote is installed automatically via npx.

Open your terminal to access the CLI.

Run this command:

claude mcp add --transport http Layer https://mcp.app.layer.ai/mcp

Launch Claude Code and run /mcp to open the MCP management panel.
Select Layer and choose Authenticate — log in with your Layer account in the browser window that opens.

If this fails with a transport error, try --transport sse instead — the correct flag depends on your Claude Code version.

Open your terminal to access the CLI.

Run this command:

codex mcp add layer -- npx -y mcp-remote@latest https://mcp.app.layer.ai/mcp

Or add to ~/.codex/config.toml manually.
OAuth triggers on first use.

Install with CursorOr manually:

Open Cursor Settings (Cmd + ,) and navigate to Features > MCP
Click + Add New MCP Server, select Streamable HTTP
Enter Name: Layer and URL: https://mcp.app.layer.ai/mcp
OAuth triggers automatically — log in with your Layer account when prompted

Step 1 — Add the Layer MCP server

Open the Command Palette (Cmd + Shift + P), search for MCP: Add Server, and select HTTP.Or add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "Layer": {
      "serverUrl": "https://mcp.app.layer.ai/mcp"
    }
  }
}

Step 2 — Authenticate

The OAuth flow will trigger automatically — log in with your Layer account when prompted.

Step 3 — Verify it works

Ask: “What can I do with Layer?”

Open your terminal to access the CLI.

Run this command:

gemini mcp add --transport http Layer https://mcp.app.layer.ai/mcp

Or add to ~/.gemini/settings.json manually.
OAuth triggers on first use.

Install with VS CodeOr manually add to .vscode/mcp.json:

{
  "servers": {
    "Layer": {
      "type": "http",
      "url": "https://mcp.app.layer.ai/mcp"
    }
  }
}

OAuth triggers on first use — log in with your Layer account when prompted.

Open your terminal to access the CLI.

Run this command:

amp mcp add layer https://mcp.app.layer.ai/mcp

OAuth authentication via Dynamic Client Registration.

Edit ~/.config/opencode/opencode.json:

{
  "mcp": {
    "Layer": {
      "type": "remote",
      "url": "https://mcp.app.layer.ai/mcp"
    }
  }
}

OAuth triggers automatically on first use — log in with your Layer account when prompted.

Open Settings > AI > Manage MCP servers > + Add > CLI Server.

Enter this command:

npx -y mcp-remote@latest https://mcp.app.layer.ai/mcp

OAuth triggers on first use.

Zed only supports stdio transport. Use mcp-remote as a bridge.Add to ~/.config/zed/settings.json:

{
  "context_servers": {
    "Layer": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.app.layer.ai/mcp"
      ]
    }
  }
}

OAuth triggers automatically on first use — log in with your Layer account when prompted.

Connect using a Personal Access Token (PAT) — works with any MCP client.First, generate a PAT in Layer: go to User Settings > New Token and copy the token (starts with pat_).

Open Settings > Developer > MCP Servers.

Add this config (replace YOUR_PAT with your token):

{
  "mcpServers": {
    "Layer": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.app.layer.ai/mcp",
        "--header",
        "Authorization: Bearer YOUR_PAT"
      ]
    }
  }
}

Requires Node.js. mcp-remote is installed automatically via npx.

Open your terminal to access the CLI.

Run this command, replacing YOUR_PAT with your token:

claude mcp add --transport http Layer https://mcp.app.layer.ai/mcp --header "Authorization: Bearer YOUR_PAT"

Verify by asking: “What can I do with Layer?”

Open your terminal to access the CLI.

Replace YOUR_PAT with your token, then run:

codex mcp add layer -- npx -y mcp-remote@latest https://mcp.app.layer.ai/mcp \
  --header "Authorization: Bearer YOUR_PAT"

Verify by asking: “What can I do with Layer?”

Step 1 — Add the Layer connector

In Manus, go to Personalization > Connectors, click Add connector, then select Custom MCP > Import by JSON and paste:

{
  "mcpServers": {
    "Layer": {
      "type": "streamableHttp",
      "url": "https://mcp.app.layer.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PAT"
      }
    }
  }
}

Replace YOUR_PAT with your token and click Save.

Step 2 — Verify it works

Click the Try it out button — Manus will open a prompt to test the connection and show you Layer’s capabilities.

Step 1 — Add the Layer MCP server

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "Layer": {
      "url": "https://mcp.app.layer.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PAT"
      }
    }
  }
}

Replace YOUR_PAT with your token.

Step 2 — Verify it works

Ask: “What can I do with Layer?”

Step 1 — Add the Layer MCP server

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "Layer": {
      "serverUrl": "https://mcp.app.layer.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PAT"
      }
    }
  }
}

Replace YOUR_PAT with your token.

Step 2 — Verify it works

Ask: “What can I do with Layer?”

Open your terminal to access the CLI.

Run this command, replacing YOUR_PAT with your token:

gemini mcp add --transport http --header "Authorization: Bearer YOUR_PAT" Layer https://mcp.app.layer.ai/mcp

Or add to ~/.gemini/settings.json manually with the Authorization header.
Verify by asking: “What can I do with Layer?”

Step 1 — Add the Layer MCP server

Add to .vscode/mcp.json:

{
  "servers": {
    "Layer": {
      "type": "http",
      "url": "https://mcp.app.layer.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PAT"
      }
    }
  }
}

Replace YOUR_PAT with your token.

Step 2 — Verify it works

Ask: “What can I do with Layer?”

Edit ~/.config/opencode/opencode.json:

{
  "mcp": {
    "Layer": {
      "type": "remote",
      "url": "https://mcp.app.layer.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PAT"
      }
    }
  }
}

Replace YOUR_PAT with your token.

Step 1 — Add the Layer MCP server

Add to ~/.config/zed/settings.json:

{
  "context_servers": {
    "Layer": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.app.layer.ai/mcp",
        "--header",
        "Authorization: Bearer YOUR_PAT"
      ]
    }
  }
}

Replace YOUR_PAT with your token.

Step 2 — Verify it works

Ask: “What can I do with Layer?”

Available tools

The MCP server exposes the following tools. Your AI agent selects and calls them automatically based on your prompts.

Instructions

Tool	Description
`get_instructions`	Returns platform guidance, Creative Unit pricing info, and error codes
`get_workflow_instructions`	Returns the full workflow lifecycle: discover, estimate, execute, poll, display
`get_forge_instructions`	Returns the forge (direct model execution) lifecycle

These are called automatically to understand how to use the platform. You don’t need to invoke them directly.

Workspaces

Tool	Description
`list_workspaces`	List all workspaces you belong to, including Creative Unit balances
`get_workspace`	Get details for a specific workspace

Models

Tool	Description
`get_model_recommendations`	Get curated model recommendations by category
`list_models`	Search and filter models by modality, capabilities, or text query
`get_model`	Get full details for a model including capabilities and prompt format

Models can be filtered by modality (image, video, three_d, audio) and by capabilities like inpainting, style_reference, text_to_3d, lipsync, and more.

Workflows

Workflows are multi-step pipelines built in the Layer app’s Blueprint editor.

Tool	Description
`list_workflows`	List available workflows with their inputs and outputs
`estimate_workflow_price`	Check the Creative Unit cost before running
`execute_workflow`	Run a workflow (async — returns a `run_id`)
`get_workflow_run`	Poll for workflow run status and results
`cancel_workflow_run`	Cancel a running workflow and release reserved CUs

Forge (direct model execution)

Forge runs a single model directly, giving you full control over parameters.

Tool	Description
`estimate_forge_price`	Check the Creative Unit cost for a generation
`execute_forge`	Run inference on a model (async — returns an `inference_id`)
`get_forge_run`	Poll for forge run status and generated assets

Forge supports the full range of generation parameters: prompts, dimensions, batch size, guidance files (reference images, masks, poses, depth maps), video effects, 3D options, audio settings, and post-processing (upscale, vectorize, remove background).

Files

Tool	Description
`request_file_upload_url`	Get a signed upload URL for a local file (image, video, or audio)
`upload_file`	Upload a file from a public URL for use as input in workflows or forge

request_file_upload_url supports PNG, JPEG, WebP (up to 100 MB), MP4 (up to 5 GB), and WAV/MP3 (up to 64 MB). upload_file supports PNG, JPEG, WebP, and MP4 (up to 64 MB).

request_file_upload_url is available in Claude Code CLI and similar clients. It does not work in Claude.ai or Claude Desktop due to URL allowlisting restrictions.

Example prompts

Once connected, try prompts like:

“Generate 4 variations of a crystal sword icon on a transparent background”
“Show me what image models are available for my workspace”
“Create a 3D model of a treasure chest from this reference image”
“Run the product shot workflow with a photo of my item”
“How many Creative Units do I have left?”

Your AI agent will pick the right tools, estimate costs, run the generation, and show you the results.

Error codes

Code	Status	Meaning
`UNAUTHENTICATED`	401	OAuth connection not completed — reconnect in your Connectors settings
`FORBIDDEN`	403	You don’t have permission for this action
`INSUFFICIENT_BALANCE`	402	Not enough Creative Units — top up in Settings > Billing
`RATE_LIMITED`	429	Max 5 concurrent runs per user per workspace
`WORKSPACE_NOT_FOUND`	404	Workspace doesn’t exist or you’re not a member
`MODEL_NOT_FOUND`	404	Model not found or not available in this workspace
`WORKFLOW_NOT_FOUND`	404	Workflow not found or not linked to this workspace
`RUN_NOT_FOUND`	404	Workflow or forge run doesn’t exist
`INVALID_INPUTS`	400	Malformed parameters or UUIDs
`UPLOAD_FAILED`	400	File could not be downloaded or stored

Troubleshooting

Layer doesn’t appear in my Connectors list (Claude) Your team admin needs to add the custom connector first. If you’re on a personal account, make sure you’re looking under Customize > Connectors. Authorization fails or times out Make sure you have an active Layer account at layer.ai. If you’re behind a VPN or corporate firewall, the OAuth redirect may be blocked — try on a direct connection. Agent doesn’t seem to use Layer tools Start a new conversation after connecting — existing conversations may not pick up new MCP servers. Check that the connector status shows as connected. Claude Code: “unknown transport” error Try --transport sse instead of --transport http — the correct flag depends on your Claude Code version. Codex: MCP server not loading Make sure mcp-remote is installed correctly. Try running npx -y mcp-remote@latest to verify. If using API Key, ensure the LAYER_PAT environment variable is set in your shell profile and you’ve restarted Codex. Cursor / VS Code / Windsurf: connection fails Verify the MCP server URL is exactly https://mcp.app.layer.ai/mcp. If using API Key, check that the Authorization header value starts with Bearer (with a space) followed by your token. Manus: tools not working Verify that your Personal Access Token is valid and the Authorization header value starts with Bearer (with a space) followed by your token. Make sure the transport type is streamableHttp in the JSON config. Gemini CLI: authentication error If using API Key, ensure the header flag is formatted correctly: --header "Authorization: Bearer YOUR_PAT". If using OAuth, the flow should trigger automatically on first tool use.

Getting started

​Connect to Layer

​Step 1 — Add the Layer MCP server

​Step 2 — Authenticate

​Step 3 — Verify it works

​Step 1 — Add the Layer connector

​Step 2 — Verify it works

​Step 1 — Add the Layer MCP server

​Step 2 — Verify it works

​Step 1 — Add the Layer MCP server

​Step 2 — Verify it works

​Step 1 — Add the Layer MCP server

​Step 2 — Verify it works

​Step 1 — Add the Layer MCP server

​Step 2 — Verify it works

​Available tools

​Instructions

​Workspaces

​Models

​Workflows

​Forge (direct model execution)

​Files

​Example prompts

​Error codes

​Troubleshooting

Connect to Layer

Step 1 — Add the Layer MCP server

Step 2 — Authenticate

Step 3 — Verify it works

Step 1 — Add the Layer connector

Step 2 — Verify it works

Step 1 — Add the Layer MCP server

Step 2 — Verify it works

Step 1 — Add the Layer MCP server

Step 2 — Verify it works

Step 1 — Add the Layer MCP server

Step 2 — Verify it works

Step 1 — Add the Layer MCP server

Step 2 — Verify it works

Available tools

Instructions

Workspaces

Models

Workflows

Forge (direct model execution)

Files

Example prompts

Error codes

Troubleshooting