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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LYRIA_MODELNoThe Lyria model to use for audio generation, e.g. lyria-3.5.
GEMINI_API_KEYNoGoogle AI API key required for the generate_audio tool. Not passed to tool inputs or JSON outputs.
KIHACHI_MEMORY_PATHNoPath to the memory file to persist memory across restarts. If unset, memory is held only in-process.

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
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}

Tools

Functions exposed to the LLM to take actions

NameDescription
helloA

Return a simple health-check greeting.

generate_songspecB

Generate a SongSpec via Brain, filling omitted values from knowledge.

create_project_from_songspecC

Build a ProjectPlan, optionally including its arrangement.

create_ableton_planC

Translate a ProjectPlan JSON value into an Ableton plan.

execute_live_requestC

Attempt an approved Live request through the configured adapter boundary.

prepare_ableton_handoffA

Validate an Ableton plan before a future Live handoff.

request_live_executionA

Prepare one approval-gated Live mutation request without executing it.

generate_audioC

Generate one audio target through the configured Google Lyria boundary.

review_songspecC

Review a SongSpec through the Brain review boundary.

remember_songC

Remember a SongSpec and optional ReviewResult.

search_memoryC

Search memory by genre and optional review quality filters.

orchestrate_songC

Run generation, review, memory, and project preparation.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.2/5.0

Scored across 12 tools

Disambiguation4/5

Most tools map cleanly to distinct pipeline stages: spec generation, review, audio generation, project planning, Ableton planning, and memory operations. The pairs execute_live_request/request_live_execution and create_ableton_plan/prepare_ableton_handoff create mild ambiguity, but their descriptions clarify intent. Overall, an agent can usually select the right tool without much trouble.

Naming Consistency4/5

All tools except hello follow a clear snake_case verb_noun pattern using domain-specific objects like songspec, project, plan, audio, and memory. hello is a minor exception, reading more like a interjection than a verb_noun action, but it is semantically a health check. This is very close to fully consistent naming.

Tool Count5/5

Twelve tools is well within the expected range for a focused domain and maps to a coherent music-generation lifecycle. Each tool serves a meaningful role whether that is orchestration, individual pipeline stages, or memory access. There is no obvious bloat or redundancy.

Completeness4/5

The surface covers the main workflow: generate, review, audio generation, project planning, Ableton planning, approval-gated execution, memory storage/retrieval, and orchestration. Gaps like direct retrieval/update/delete of remembered artifacts or editing existing plans would require workarounds but are not dead ends. Core user journeys are coherent and actionable.

Maintenance

ActivityMaintained
ResponsivenessNo issues