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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
COMFY_URLNoThe headless ComfyUI instance URL.http://127.0.0.1:8188
COMFY_OUTPUT_DIRYesMust match the --output-directory ComfyUI was launched with; the server reads generated PNGs straight off this path.
ARTIFICER_TIMEOUT_MSNoPer-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

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
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 anatomy line from the book; the result reports anatomy. Every kind runs on flash by default; tier: "pro" refuses without confirmPro: true and states the cost. Returns the file path, dimensions, and estimated spend.

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 anatomy line from the book; the result reports anatomy: what it found, each flaw placed in the picture, and for a token the rotation that brings its front to the top. Props (kind "prop") get object-only wording (no figures added) and come back cut at the source file's exact pixel size, ready for the same tile slot. Battlemaps (kind "battlemap") restyle a bought map with the layout locked: the result lands on the source's pixel grid (a whole-number upscale when the source is small), is checked for drift against the source (a drifted render is redone once, then refused), and comes with a checkerboard image of source and result to eyeball. A dressing pass (dressing: true, battlemaps only) adds furniture and props, which the check reads as moved layout, so it renders once and reports drift without retrying or refusing. Overland maps (kind "overland") repaint a regional or world map the same way, painted bare of every name, marker, road, compass rose and scale bar (letter them on afterwards), with a looser drift check that refuses only a grossly moved geography. Returns the new file path, dimensions, and estimated spend.

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

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.2/5.0

Scored across 4 tools

Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count5/5

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.

Completeness4/5

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.

Maintenance

ActivityActive
ResponsivenessWithin a week