Levelry MCP — Visual Canvas for AI Agents

Connect AI agents to a visual knowledge base via the Model Context Protocol. Includes a ready-made SKILL.md for instant agent setup with Claude, GPT, Hermes, or any MCP-compatible tool.

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What is Levelry?

Levelry is a visual knowledge base platform built around:

• Canvas — an infinite visual workspace where ideas live in space
• Objects — every canvas object is also a full document (not just a label)
• Layers — separate concerns (narrative, economy, tasks) without losing the big picture
• AI Copilot — contextual AI that understands your canvas and selects the right skills per task
• Skills — modular AI behaviors (balance analysis, creative ideation, etc.)
• MCP — Model Context Protocol for AI agent integration

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MCP Server

Endpoint: https://levelry-server-hvyc5.ondigitalocean.app/mcp

Transport: HTTP + SSE

Auth: Bearer token — user-specific, scoped to your Levelry account.

See Getting Your MCP Token below for setup instructions.

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What You Can Do with MCP

Capability	Description
Read canvas state	List objects, search documents, read project metadata
Write to canvas	Create objects, update positions and content, connect objects
Multi-project	Switch between projects without reconnecting
Layer management	Place content on specific layers, move objects between layers
Batch operations	Create up to 100 objects at once, update up to 200

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Quick Example

{
  "toolName": "searchDocuments",
  "params": { "query": "combat system", "limit": 10 }
}

{
  "toolName": "createMultipleObjects",
  "params": {
    "objects": [
      { "emoji": "⚔️", "x": 1500, "y": 1250, "name": "Combat System", "content": "Core combat mechanics" },
      { "emoji": "❤️", "x": 1700, "y": 1250, "name": "Health", "content": "HP and damage formulas" }
    ],
    "connections": [{ "from": 0, "to": 1 }]
  }
}

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Use Cases

Research & Lookup

"What do we have on the boss fight design?" — semantic search across all object documents and names.

Structured Capture

"Add this mechanic to the canvas" — place a new object with full documentation right where it belongs visually.

Visual Mapping

"Connect these systems" — create objects and link them with visual connections to map dependencies.

AI-Assisted Design

"Analyze balance on this layer" — AI copilot reads canvas context and applies domain-specific skills.

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Architecture

AI Agent (MCP-compatible)
  └── Levelry MCP Client
        └── Levelry MCP Server
              └── Levelry Canvas API
                    └── Levelry Platform

The MCP server translates tool calls into Levelry REST API requests. The agent never calls the API directly.

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Getting Your MCP Token

Open Levelry, go to the menu and click MCP. The settings dialog has two tabs:

OAuth Setup (recommended for agentic coding tools)

Guides for different MCP-compatible tools are available directly in the app. OAuth flow:

1. Click the auth link provided by Levelry
2. Authorize access — select the initial project (you can switch projects at any time later)
3. Grant permission level: read-only or read-write

API Key Setup (recommended for autonomous agents)

For standalone agents like OpenClaw or Hermes:

1. Generate a Bearer token directly in the app
2. Copy the ready-to-use config snippet
3. Set permission scope for this key (read-only or read-write)

Quick Config

# OAuth or API key — both use the same config field
levelry:
  mcp_token: "<your_token>"

Restart the agent after adding the token — Levelry tools will appear automatically.

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The Skill

The levelry-mcp-guide skill teaches any AI agent how to work with Levelry. It covers canvas fundamentals (bounds, layers, objects), document conventions, MCP tool limits, and best practices for placement and batch operations.

Install in Your Project

npx skills add kt3v/levelry-docs --skill levelry-mcp

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weird_drop by [indie indie]