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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
IMAGE_MODELNo生图模型,回退 VISION_MODEL
VISION_MODELYes默认视觉模型
VISION_API_KEYYes视觉 Key
VISION_API_BASE_URLYes视觉 API 根地址
VISION_BACKUP_MODELNoocr 备用视觉模型,回退 VISION_MODEL
VISION_ANALYZE_MODELNoanalyze 专用模型,回退 VISION_MODEL

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
{
  "listChanged": true
}
logging
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
vision_analyzeA

Understand, explain, or describe an image using a vision model. Use for interpreting screenshots, UI, diagrams, charts, or error messages that need reasoning. Not for verbatim text extraction (use vision_ocr).

vision_ocrA

Extract exact text from an image (OCR). Use when the user wants literal text copied verbatim from a screenshot, code image, terminal output, document, or receipt. Not for explaining or understanding images (use vision_analyze).

image_generateA

Generate one or more images from a text prompt through an OpenAI-compatible images/generations endpoint. Images are returned inline as base64 when available, otherwise as download URLs.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.4/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: vision_analyze for understanding/explaining images, vision_ocr for verbatim text extraction, and image_generate for creating images. The descriptions explicitly cross-reference each other to prevent confusion, leaving no ambiguity.

Naming Consistency4/5

The naming is mostly consistent with a domain prefix and action (vision_analyze, vision_ocr), but image_generate deviates by using 'image_' instead of 'vision_'. This is a minor inconsistency that does not hinder readability, but it is a noticeable break from the established pattern.

Tool Count5/5

Three tools is a well-scoped count for a vision server, covering analysis, OCR, and generation. Each tool addresses a distinct core capability, and there are no redundant or missing tools that would suggest over- or under-engineering.

Completeness5/5

For the stated domain of vision tasks, the tool surface is complete: understanding (analyze), text extraction (OCR), and creation (generate). There are no obvious missing operations that would force an agent into a dead end; the tools cover the primary workflows one would expect from a vision server.

Maintenance

ActivitySlowing
ResponsivenessNo issues