Categories › AI & Agents › Models, LLM APIs, routing, serving, training & GPUs
AI model/agent directory with pricing and comparisons, plus GPU VRAM fit and tokens/sec estimates.
Remote server: your requests and data go to softperceptron.com. Claude Code: claude mcp add --transport http softperceptron https://softperceptron.com/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
search_ai_models — Search the SoftPerceptron directory of AI models, autonomous agents and token/credit products. Returns pricing, specs and provider for each get_ai_model — Get full details for one directory entry by id or common alias (e.g. 'claude', 'gpt', 'gemini'). Returns pricing, specs, provider and links.compare_ai_models — Compare two directory entries side by side — pricing, context window, modality and what each is best for. Both must be the same kind (model can_i_run_model — Check whether a specific open-weight model fits on a specific GPU: VRAM required, whether it fits, how much headroom, which quantization to list_local_models — List the open-weight models supported by the VRAM/can-i-run calculator, with parameter counts and what each is good for.list_gpus — List the GPUs supported by the VRAM calculator, with VRAM, memory bandwidth and power draw.Not tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.