LC

LLM Configurator

io.github.aikuba/llmconfigurator

Read-only: which local LLMs a GPU or Mac can run - VRAM fit, tokens/sec, model specs.

Yes, your AI can use this right now.Answered a live MCP handshake in 327 ms with no sign-in needed and exposes 5 tools.

Connect it

Settings → Connectors → Add custom connector
URL: https://elgadmisijrfowuujcmu.supabase.co/functions/v1/mcp

5 tools, verified live

Pulled straight from the server with tools/list on 2026-10-17.
search_catalogread-only

Use this first when the user names a GPU, Mac, mini PC or language model and you need its id for the other tools. Matches names and common aliases in a fixed catalogue of local-LLM hardware and models. It does not return specs, fit or speed, and it does not search the web.

check_hardware_fitread-only

Use this when the user asks whether one specific model runs on one specific machine, at what memory cost, and roughly how fast. Needs a hardware id and a model id from search_catalog. Returns a fit verdict, the memory arithmetic, and a decode-speed range with a confidence label. Memory is sized from all parameters, speed from active parameters. It does not recommend purchases and does not run anyt

models_for_hardwareread-only

Use this when the user asks what models a given machine can run. Needs a hardware id from search_catalog. Returns up to 20 catalogue models ranked for that machine, each with a fit verdict and a speed range, optionally filtered to one use such as coding. It covers only models in the catalogue, at one quantisation and context length per call, and leaves out models that do not fit.

compare_hardwareread-only

Use this when the user compares two to four machines. Needs hardware ids from search_catalog. Returns memory, bandwidth, memory type, release year, status and a dated price where one is recorded, side by side. A price of null means none is on record. It does not check any model against the machines; use check_hardware_fit for that.

get_model_specsread-only

Use this when the user asks about one model's size, architecture, context window or licence. Needs a model id from search_catalog. Returns total and active parameters, weight size per quantisation, context length, licence, release date and sources. It does not say whether the model fits any machine; use check_hardware_fit for that.

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