Schema | Train in Silence

Train in Silence

Describes the environment variables required to run the server.

Name	Required	Description	Default
No arguments

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.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": false }
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
planner_metadataA	Return MCP server metadata and the exposed planner capabilities.
validate_requestB	Validate a planning request provided inline or loaded from a YAML/JSON config path.
recommend_hardwareC	Generate ranked hardware recommendations for an LLM fine-tuning planning request.
explain_planA	Run the full planner and return estimates, normalized market offers, and provider statuses. WARNING: This tool returns raw market data and is extremely verbose (often 100k+ tokens). Use recommend_hardware for standard recommendation tasks.
list_providersC	Fetch provider health statuses using optional planning constraints.
probe_marketC	Run market aggregation for a planning request and return provider statuses.
dump_market_offersC	Return normalized market offers considered for a planning request.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/hlpun/Train-in-Silence'

If you have feedback or need assistance with the MCP directory API, please join our Discord server