MAGI Orchestrator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | No | API key for Gemini | |
| OPENAI_API_KEY | No | API key for OpenAI | |
| ANTHROPIC_API_KEY | No | API key for Anthropic Claude |
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 |
|---|---|
| run_magi_iterationA | Execute one MAGI iteration for a task using |
| get_magi_statusA | Retrieve MAGI runtime status, default agent, available agent adapters, and resolved state directory. |
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 2 tools
get_magi_status and run_magi_iteration have clearly distinct purposes: one retrieves runtime status, the other executes an iteration. No overlap or ambiguity.
Both tools follow a consistent verb_noun pattern: get_magi_status and run_magi_iteration, using snake_case throughout.
With only 2 tools, the server feels thin for an 'Orchestrator' concept. However, the tools cover basic status and execution, so it is borderline appropriate.
The tool surface lacks many expected operations for an orchestrator, such as agent management, task listing, or configuration. Significant gaps exist.