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sachinuppal

ModelCostSaver

by sachinuppal
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
MODELCOSTSAVER_LEDGERNoEnable the local record_usage write. Default is 'off'.
MODELCOSTSAVER_REFRESHNoEnable the opt-in remote catalog refresh. Default is 'off'.
MODELCOSTSAVER_PROVIDERNoBias select_optimal_model toward a specific provider. Default is none.
MODELCOSTSAVER_PROVIDERSNoAllowlist for recommendations (e.g., 'anthropic,openai'). Default is client-derived.
MODELCOSTSAVER_TELEMETRYNoTelemetry setting (kept off for transparency). Default is 'off'.
MODELCOSTSAVER_FAST_MODELNoPin a preferred model for the fast tier. Default is catalog cheapest.
MODELCOSTSAVER_CATALOG_URLNoOverride the refresh source URL. Default is bundled.
MODELCOSTSAVER_INCLUDE_LOCALNoSurface self-hosted / $0 models. Default is 'off'.
MODELCOSTSAVER_TRIVIAL_MODELNoPin a preferred model for the trivial tier. Default is catalog cheapest.
MODELCOSTSAVER_STANDARD_MODELNoPin a preferred model for the standard tier. Default is catalog cheapest.
MODELCOSTSAVER_CHARS_PER_TOKENNoTune the token estimator. Default is '4'.
MODELCOSTSAVER_REASONING_MODELNoPin a preferred model for the reasoning tier. Default is catalog cheapest.

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
}
prompts
{
  "listChanged": true
}
resources
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
estimate_costA

Estimate the cost of a single LLM call for one model from known or estimated token counts. Offline, no keys.

predict_costA

Forecast the cost of a prompt across candidate models before the call. Returns a cheapest-first ranking with assumptions. Offline.

select_optimal_modelB

Pick the single cheapest model that meets the task tier, capabilities, and budget, with full reasoning and a fallbackChain. Offline.

compare_modelsB

Compare models side by side for a fixed token shape, cheapest first, with the multiple of the cheapest. Offline.

list_modelsB

Return the model catalog with pricing, optionally filtered. capabilities are arrays. Offline.

get_pricingC

Return the model catalog with pricing, optionally filtered. capabilities are arrays. Offline.

optimize_requestA

Check whether a cheaper capable model exists for a call you plan to make, and report the savings. Offline.

Prompts

Interactive templates invoked by user choice

NameDescription
modelcostsaverHow and when to use ModelCostSaver: forecast cost and pick the cheapest capable model before an LLM call.
modelcostsaver-setupSelf-configure ModelCostSaver in this client. Hand this to your agent to set it up.

Resources

Contextual data attached and managed by the client

NameDescription
catalogThe full model catalog with per-token pricing, tiers, and capabilities. Offline, versioned.

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