fvtt-mcp-artificer
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| COMFY_URL | No | The headless ComfyUI instance URL. | http://127.0.0.1:8188 |
| COMFY_OUTPUT_DIR | Yes | Must match the --output-directory ComfyUI was launched with; the server reads generated PNGs straight off this path. | |
| ARTIFICER_TIMEOUT_MS | No | Per-job wait cap for ComfyUI jobs. | 300000 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate-imageA | Generate one Foundry art asset from a prompt via the Gemini image API. kind picks the model tier, aspect, size, framing text, and post-processing; the result is a finished PNG on disk. READ IT before showing anyone: count limbs per creature, check for duplicated spell effects or props, stray signatures, and reference faces on the wrong figure; obvious flaws are one edit-image call away. Every token and portrait render is also counted by a judge model (heads, eyes, limbs, hands and fingers, tails, tendrils, held objects, and a token's facing) against an optional |
| edit-imageA | Edit an existing image with one instruction while keeping identity, pose, angle, and style. Flash for every kind (pro was no better at fixes and re-cropped once). Tokens are prompted light (your instruction as you would type it in the Gemini app, plus a keep-face/hair/angle line and "remove any cast shadow"), put back on a chroma plate keyed to the token's own colours, and cut to alpha on the 512 square in the same call. "give this an updated painterly style" restyles a world token in place; a token from any library or a capture of your own is restyled the same way, its pose and camera kept. Every token and portrait edit is counted by a judge model (heads, eyes, limbs, hands and fingers, tails, tendrils, held objects, and a token's facing) against an optional |
| cutout-imageA | Knock the background off a token image to real alpha and deliver it centred on a 512 square so Foundry scale 1.0 is right. Writes a magenta-composited *_preview.png beside it: READ THAT before trusting the edge. Returns coverage, residual-key and haze numbers; a cut that fails any of them falls back to the rembg AI matte automatically. |
| imagegen-statusA | Setup doctor and health check: API key present and accepted (no generation credit spent), which image models the key can reach, the output directory (writable, outside any git repo), the cutout Python (Pillow, numpy, rembg), and estimated session spend by tier. Call this first on a cold start. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a distinct role: generate-image creates new assets, edit-image modifies existing assets, cutout-image performs alpha extraction, and imagegen-status checks setup/spend. The generate vs. edit boundary is clear, and cutout/status do not overlap with either. Descriptions reinforce the distinctions with specific use cases.
Three tools follow a clear verb_noun hyphenated pattern: generate-image, edit-image, cutout-image. imagegen-status is the minor deviation, using a noun-style status label rather than verb_noun. Overall the convention is predictable and readable.
Four tools is well-scoped for an image-generation and processing server. Each tool covers a necessary step: create, edit, cut out, and diagnose/status. No tool appears redundant or trivial.
The surface covers the core lifecycle: generate, edit/restyle, cutout, and health/status. Minor gaps exist around asset listing, deletion, batch operations, or variant management, but the main Foundry art workflows are supported. Agents can work around the missing convenience operations.