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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
CUSTOM_MODELYesModel ID for the custom provider, e.g. qwen3-coder
DZ23_ROTATIONYesModel rotation list, e.g. custom:qwen3-coder
CUSTOM_BASE_URLYesBase URL for the custom OpenAI-compatible server, e.g. http://127.0.0.1:11434/v1
DZ23_ALLOW_PAIDNoSet to false to block paid and low-cost categories. Categories mixed and free-tier may still incur costs.

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": false
}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_modelsC

List configured routing targets, tiers and declared capabilities

provider_inventoryB

Inventory all registered providers without exposing secrets

discover_modelsC

Discover models from provider /models endpoints

health_checkB

Probe configured providers/models in parallel

project_initC

Create/update canonical shared project memory

mission_statusC

Read shared mission state and recent journal events

memory_checkpointC

Persist a handoff checkpoint for another harness/agent

delegateC

Delegate one task with automatic provider failover and context continuity

consensusC

Ask multiple independent models/reviewers

swarm_runC

Run parallel specialist subagents; multiple workers may share a provider

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

C2.9/5.0

Scored across 10 tools

Disambiguation4/5

Tools mostly target distinct resources and actions: provider/model inventory, health, memory, delegation, consensus, and swarm execution. However, list_models and discover_models both return model lists and could be confused, and consensus vs swarm_run both orchestrate multiple models/subagents. Descriptions differentiate them, but boundaries are not perfect.

Naming Consistency3/5

All names use snake_case, but patterns vary: verb_noun (list_models, discover_models), noun_noun (provider_inventory, health_check, mission_status, memory_checkpoint), noun_verb (project_init, swarm_run), and bare verbs/nouns (delegate, consensus). The inconsistency is readable but not predictable.

Tool Count5/5

10 tools is well within the typical 3-15 range for an orchestration server. Each tool covers a distinct capability area: provider/model management, health, project memory, delegation, consensus, and swarms.

Completeness4/5

Core workflows for provider/model discovery, health, project memory, mission status, delegation, consensus, and swarm execution are present. Missing or unclear operations include aborting/canceling a running delegate/swarm, dynamically adding/removing providers, and richer mission listing, but these are minor for the apparent scope.

Maintenance

ActivityMaintained
ResponsivenessNo issues