loenn-mcp 3.0.1

Celeste map editor for AI agents — MCP server for reading, editing, and previewing .bin map files

loenn-mcp

Celeste map editor for AI agents — a Model Context Protocol (MCP) server that lets GitHub Copilot, Claude, and other MCP clients read, edit, analyze, procedurally generate, and preview Celeste .bin map files without ever opening Lönn.

Built for use with Everest mods. Works with maps created by Lönn or Ahorn.

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Features

28 MCP tools across 7 categories

Map Reading

Tool	Description
list_maps	List all .bin files in the project
read_map_overview	Summary of rooms, entities, triggers, and stylegrounds
read_room	Full detail for a single room: tiles, entities, triggers, decals
get_room_tiles	Raw tile grid (foreground or background) for a room

Map Editing

Tool	Description
add_entity	Place an entity in a room (auto-assigns ID)
remove_entity	Delete an entity by ID
add_trigger	Place a trigger (rectangular region) in a room, with optional path nodes
remove_trigger	Delete a trigger by ID
set_room_tiles	Replace the tile grid for a room
add_room	Create a new room with custom position/size
remove_room	Delete a room from the map
create_map	Create a new empty .bin map file

Stylegrounds

Tool	Description
list_stylegrounds	List foreground + background effects (with indices)
add_styleground	Add an effect (parallax, custom Lua effect, apply group, etc.) to FG or BG
remove_styleground	Remove an effect by index
update_styleground	Merge property changes into an existing effect

Entity / Trigger Catalog

Tool	Description
list_entity_definitions	Browse Lönn entity .lua files in the project
get_entity_definition	Read the full source of a single entity definition
list_trigger_definitions	Browse Lönn trigger .lua files
list_effect_definitions	Browse Lönn effect .lua files

Analysis

Tool	Description
analyze_map	Statistics: entity counts, type breakdown, world bounds
visualize_map_layout	ASCII mini-map of room positions
preview_map_section	Detailed ASCII preview of a map region

Rendering

Tool	Description
render_map_html	Interactive HTML preview (zoom, pan, room details, minimap, search)

Procedural Generation (NEW in v2)

Tool	Description
build_pattern_library	Scan local .bin maps and extract room patterns into a reusable JSON library
generate_room_from_pattern	Generate a new room using patterns + a strategy + seed
validate_room	Check a room for playability issues (spawn, floor, bounds)
ingest_external_map	Download maps from external URLs (GameBanana etc.) and extract patterns

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Quick Start

1 — Install from PyPI

pip install loenn-mcp

Or clone and install from source:

git clone https://github.com/Maggy-Studio/loenn-mcp
cd loenn-mcp
pip install -e .

2 — Connect to GitHub Copilot (VS Code)

Add to your project's .vscode/mcp.json:

{
  "servers": {
    "loenn-mcp": {
      "type": "stdio",
      "command": "python",
      "args": ["-m", "loenn_mcp.server"],
      "env": {
        "LOENN_MCP_WORKSPACE": "${workspaceFolder}"
      }
    }
  }
}

Then ask Copilot things like:

• "What rooms are in 01_City_A.bin?"
• "Add a strawberry to room a-03 at position (120, 80)"
• "Render an HTML preview of 07_Hell_A.bin and open it"
• "Build a pattern library from all my maps, then generate 5 challenge rooms"

3 — Connect to Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "loenn-mcp": {
      "command": "python",
      "args": ["-m", "loenn_mcp.server"],
      "env": {
        "LOENN_MCP_WORKSPACE": "/absolute/path/to/your/mod"
      }
    }
  }
}

4 — One-click map preview (standalone)

python -m loenn_mcp.preview_map Maps/Maggy/Main/01_City_A.bin
python -m loenn_mcp.preview_map Maps/Maggy/Main/01_City_A.bin g-   # filter rooms by prefix

The HTML preview opens in your browser and supports:

• Scroll to zoom, drag to pan, pinch on touch
• Click a room → detail panel (entities, triggers, size)
• Live search filter (F to focus)
• Minimap with viewport indicator
• Keyboard shortcuts: + / - zoom, 0 fit, Esc deselect

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Procedural Generation (PCG)

Generation strategies

Strategy	Description
balanced	Mix of exploration and challenge — good default
exploration	Open spaces, gentle platforming, few hazards
challenge	Dense tiles, many hazards, tight jumps
speedrun	Linear path, minimal platforms, fast flow

Model profiles

Profile	Seed behaviour	Best for
creative	Random seed each call	Maximum room variety
deterministic	Stable seed from strategy name	CI pipelines, reproducible layouts
architect	Random seed	Emphasis on room shape and connectivity

End-to-end pipeline

1. Build pattern library from existing maps
2. (Optional) ingest community maps from GameBanana
3. Create a blank map
4. Generate rooms with a chosen strategy and seed
5. Validate each room
6. Render HTML preview

Example agent prompts:

# Step 1 — build pattern library
build_pattern_library()

# Step 2 — ingest a GameBanana mod for richer pattern data
ingest_external_map(
  source_url="https://gamebanana.com/mods/53774",
  attribution="Spring Collab 2020 (various authors)",
  confirm_download=True,
  tags="community,collab"
)

# Step 3 — create map and generate rooms
create_map("Maps/PCG/MyAIMap.bin", "PCG/MyAIMap")
generate_room_from_pattern(
  map_path="Maps/PCG/MyAIMap.bin",
  room_name="a-01",
  strategy="exploration",
  seed=42,
  model_profile="deterministic"
)
generate_room_from_pattern(
  map_path="Maps/PCG/MyAIMap.bin",
  room_name="a-02",
  strategy="challenge",
  x=320
)

# Step 4 — validate
validate_room("Maps/PCG/MyAIMap.bin", "a-01")

# Step 5 — preview
render_map_html("Maps/PCG/MyAIMap.bin")

Reproducible generation (seeded)

Pass seed=<integer> and model_profile="deterministic" to get the exact same room every time:

# These two calls produce identical output:
generate_room_from_pattern(map_path="...", room_name="r1", strategy="challenge", seed=1234, model_profile="deterministic")
generate_room_from_pattern(map_path="...", room_name="r2", strategy="challenge", seed=1234, model_profile="deterministic")

GameBanana integration

ingest_external_map can fetch maps directly from GameBanana:

# Dry-run (no download) — shows what would happen
ingest_external_map(
  source_url="https://gamebanana.com/mods/53774",
  attribution="Spring Collab 2020",
  confirm_download=False
)

# Actual download + pattern extraction
ingest_external_map(
  source_url="https://gamebanana.com/mods/53774",
  attribution="Spring Collab 2020 (various authors, see mod page)",
  confirm_download=True,
  tags="expert,collab"
)

Downloaded files are saved to PCG/Datasets/ with an attribution.json file. Always verify the mod's licence permits derivative use before building on its patterns.

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Environment Variables

Variable	Default	Description
LOENN_MCP_WORKSPACE	Current working directory	Root of your Celeste mod project. The server resolves all map paths relative to this. Path traversal outside the workspace is blocked.

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How It Works

celeste_bin.py — standalone binary parser

A pure-Python implementation of the Celeste .bin map format (no Everest or Lönn required):

• Full read/write round-trip with no data loss
• Handles all 7 value types: bool, uint8, int16, int32, float32, lookup string, raw string, RLE-encoded string
• Recursive element tree matching the internal Lönn/Maple format

pcg.py — procedural generation module

New in v2. Provides:

• Pattern extraction — converts .bin rooms into reusable pattern records (size class, entity density, tile motifs, trigger usage, gameplay tags)
• Pattern library — JSON-based store with deduplication by content hash
• Strategy-based generation — balanced, exploration, challenge, speedrun modes
• Seeded randomness — random.Random(seed) for reproducible outputs; seed exposed via MCP tool parameters
• Model profiles — deterministic / creative / architect profiles control how seeds are resolved

server.py — MCP server

Built with FastMCP. All file paths are resolved relative to LOENN_MCP_WORKSPACE with path-traversal protection. Map writes are atomic (parse → mutate → write). External downloads require explicit confirm_download=True.

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Requirements

• Python 3.9+
• fastmcp >= 3.0.0

No Celeste installation required to parse, generate, or preview maps.

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License

MIT — see LICENSE.