{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_5pd4z9scekhk","handle":"readygpu-hardware-for-local-ai","url":"https://wellknown.network/agents/readygpu-hardware-for-local-ai","links":{"self":"https://wellknown.network/agents/readygpu-hardware-for-local-ai/record.json","html":"https://wellknown.network/agents/readygpu-hardware-for-local-ai","markdown":"https://wellknown.network/agents/readygpu-hardware-for-local-ai/record.md","api":"https://wellknown.network/api/v1/agents/readygpu-hardware-for-local-ai","status":"https://wellknown.network/api/v1/agents/readygpu-hardware-for-local-ai/status","claim":"https://wellknown.network/agents/readygpu-hardware-for-local-ai/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/readygpu-hardware-for-local-ai/claim.json","badge":"https://wellknown.network/agents/readygpu-hardware-for-local-ai/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/readygpu-hardware-for-local-ai/history","tools":"https://wellknown.network/api/v1/agents/readygpu-hardware-for-local-ai/tools"},"ard":{"identifier":"urn:air:readygpu.com:server:readygpu-hardware-for-local-ai","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"readygpu: hardware for local AI","summary":"Live UK, Germany, Canada and US prices for GPUs and Macs that run open AI models. No sign-up.","description":"Live UK, Germany, Canada and US prices for GPUs and Macs that run open AI models. No sign-up.","publisher":{"name":"com.readygpu","url":null},"homepage":"https://readygpu.com","repository":null,"version":"1.0.0","license":null,"protocols":["mcp"],"tags":[],"pricing":null,"endpoints":[{"url":"https://readygpu.com/api/mcp","type":"mcp_streamable_http","auth":null,"probeable":true}],"skills":null,"tools":null,"extra":{"updatedAt":"2026-10-27T06:59:34.254464Z","publishedAt":"2026-10-27T06:59:34.254464Z","registryName":"com.readygpu/readygpu"},"attribution":{"kind":"mcp_registry","name":"mcp_registry","summary":"mcp_registry","version":"mcp_registry","description":"mcp_registry","homepageUrl":"mcp_registry","publisherName":"mcp_registry"}},"derived":{"capabilities":[{"slug":"infra.devices","name":"Devices & IoT","confidence":1,"provenance":"derived"},{"slug":"knowledge.reasoning","name":"Reasoning & Planning","confidence":0.54,"provenance":"derived"}],"categories":["infra","knowledge"],"language":"en"},"observed":{"status":"live","statusReason":"Responded 42m ago.","lastOkAt":"2026-10-30T09:30:56.775Z","lastProbedAt":"2026-10-30T09:30:56.775Z","statusComputedAt":"2026-10-30T09:32:55.440Z","reliability30d":{"probes":6,"successRate":1,"p50Ms":89,"basis":"service","measures":{"availability":"availability","latency":"response time","tools":"tool surface observed","summary":"Checks reached the service itself."},"checks":{"total":6,"ok":6,"authBoundaryOk":0,"serviceOk":6,"note":"Counted from the observation rows for the window, checks of the server only (HTTP, A2A card, MCP initialize). ok = authBoundaryOk + serviceOk. `probes` is the sum of daily rollups and includes registry checks, so it can differ from `total`."}},"latestObservations":[{"at":"2026-10-30T09:30:56.775Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":83,"error":null,"detail":{"tools":[{"name":"search_models","description":"Find open-weight AI models by name or task (chat, coding, agentic, vision, reasoning). Returns each model's slug, size, context length and licence; use the slug"},{"name":"find_hardware","description":"List graphics cards or complete machines (Macs, mini PCs) sold in a market, with memory, bandwidth, the estimated speed on a model and a link to each one's page"},{"name":"hardware_details","description":"One graphics card or machine in a market: its specifications, which models it runs fully in memory at a context length and how fast, and a link to its page and "},{"name":"hardware_for_model","description":"For one model: how much memory it needs at each context length, and the fastest hardware (and the fastest Mac) that runs it fully in memory in a market, with th"},{"name":"best_hardware","description":"The ranked 'best for local AI' lists of a market (all graphics cards, cards under a price, used cards, Macs and mini PCs): best first by the most capable model "},{"name":"compare_hardware","description":"Two graphics cards or machines side by side in a market: memory, bandwidth, how many models each runs fully in memory, and the estimated speed of each on every "}],"toolCount":6,"toolsHash":"865e2b3c5f01291d76f147918502fb5949c5d5a450ddd8db86d356c2ead0652d","serverName":"readygpu","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-30T02:24:17.029Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":63,"error":null,"detail":{"tools":[{"name":"search_models","description":"Find open-weight AI models by name or task (chat, coding, agentic, vision, reasoning). Returns each model's slug, size, context length and licence; use the slug"},{"name":"find_hardware","description":"List graphics cards or complete machines (Macs, mini PCs) sold in a market, with memory, bandwidth, the estimated speed on a model and a link to each one's page"},{"name":"hardware_details","description":"One graphics card or machine in a market: its specifications, which models it runs fully in memory at a context length and how fast, and a link to its page and "},{"name":"hardware_for_model","description":"For one model: how much memory it needs at each context length, and the fastest hardware (and the fastest Mac) that runs it fully in memory in a market, with th"},{"name":"best_hardware","description":"The ranked 'best for local AI' lists of a market (all graphics cards, cards under a price, used cards, Macs and mini PCs): best first by the most capable model "},{"name":"compare_hardware","description":"Two graphics cards or machines side by side in a market: memory, bandwidth, how many models each runs fully in memory, and the estimated speed of each on every "}],"toolCount":6,"toolsHash":"865e2b3c5f01291d76f147918502fb5949c5d5a450ddd8db86d356c2ead0652d","serverName":"readygpu","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-29T19:30:35.091Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":105,"error":null,"detail":{"tools":[{"name":"search_models","description":"Find open-weight AI models by name or task (chat, coding, agentic, vision, reasoning). Returns each model's slug, size, context length and licence; use the slug"},{"name":"find_hardware","description":"List graphics cards or complete machines (Macs, mini PCs) sold in a market, with memory, bandwidth, the estimated speed on a model and a link to each one's page"},{"name":"hardware_details","description":"One graphics card or machine in a market: its specifications, which models it runs fully in memory at a context length and how fast, and a link to its page and "},{"name":"hardware_for_model","description":"For one model: how much memory it needs at each context length, and the fastest hardware (and the fastest Mac) that runs it fully in memory in a market, with th"},{"name":"best_hardware","description":"The ranked 'best for local AI' lists of a market (all graphics cards, cards under a price, used cards, Macs and mini PCs): best first by the most capable model "},{"name":"compare_hardware","description":"Two graphics cards or machines side by side in a market: memory, bandwidth, how many models each runs fully in memory, and the estimated speed of each on every "}],"toolCount":6,"toolsHash":"865e2b3c5f01291d76f147918502fb5949c5d5a450ddd8db86d356c2ead0652d","serverName":"readygpu","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-29T12:24:08.918Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":104,"error":null,"detail":{"tools":[{"name":"search_models","description":"Find open-weight AI models by name or task (chat, coding, agentic, vision, reasoning). Returns each model's slug, size, context length and licence; use the slug"},{"name":"find_hardware","description":"List graphics cards or complete machines (Macs, mini PCs) sold in a market, with memory, bandwidth, the estimated speed on a model and a link to each one's page"},{"name":"hardware_details","description":"One graphics card or machine in a market: its specifications, which models it runs fully in memory at a context length and how fast, and a link to its page and "},{"name":"hardware_for_model","description":"For one model: how much memory it needs at each context length, and the fastest hardware (and the fastest Mac) that runs it fully in memory in a market, with th"},{"name":"best_hardware","description":"The ranked 'best for local AI' lists of a market (all graphics cards, cards under a price, used cards, Macs and mini PCs): best first by the most capable model "},{"name":"compare_hardware","description":"Two graphics cards or machines side by side in a market: memory, bandwidth, how many models each runs fully in memory, and the estimated speed of each on every "}],"toolCount":6,"toolsHash":"865e2b3c5f01291d76f147918502fb5949c5d5a450ddd8db86d356c2ead0652d","serverName":"readygpu","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-29T04:25:39.757Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":63,"error":null,"detail":{"tools":[{"name":"search_models","description":"Find open-weight AI models by name or task (chat, coding, agentic, vision, reasoning). Returns each model's slug, size, context length and licence; use the slug"},{"name":"find_hardware","description":"List graphics cards or complete machines (Macs, mini PCs) sold in a market, with memory, bandwidth, the estimated speed on a model and a link to each one's page"},{"name":"hardware_details","description":"One graphics card or machine in a market: its specifications, which models it runs fully in memory at a context length and how fast, and a link to its page and "},{"name":"hardware_for_model","description":"For one model: how much memory it needs at each context length, and the fastest hardware (and the fastest Mac) that runs it fully in memory in a market, with th"},{"name":"best_hardware","description":"The ranked 'best for local AI' lists of a market (all graphics cards, cards under a price, used cards, Macs and mini PCs): best first by the most capable model "},{"name":"compare_hardware","description":"Two graphics cards or machines side by side in a market: memory, bandwidth, how many models each runs fully in memory, and the estimated speed of each on every "}],"toolCount":6,"toolsHash":"865e2b3c5f01291d76f147918502fb5949c5d5a450ddd8db86d356c2ead0652d","serverName":"readygpu","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-28T20:27:05.541Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":89,"error":null,"detail":{"tools":[{"name":"search_models","description":"Find open-weight AI models by name or task (chat, coding, agentic, vision, reasoning). Returns each model's slug, size, context length and licence; use the slug"},{"name":"find_hardware","description":"List graphics cards or complete machines (Macs, mini PCs) sold in a market, with memory, bandwidth, the estimated speed on a model and a link to each one's page"},{"name":"hardware_details","description":"One graphics card or machine in a market: its specifications, which models it runs fully in memory at a context length and how fast, and a link to its page and "},{"name":"hardware_for_model","description":"For one model: how much memory it needs at each context length, and the fastest hardware (and the fastest Mac) that runs it fully in memory in a market, with th"},{"name":"best_hardware","description":"The ranked 'best for local AI' lists of a market (all graphics cards, cards under a price, used cards, Macs and mini PCs): best first by the most capable model "},{"name":"compare_hardware","description":"Two graphics cards or machines side by side in a market: memory, bandwidth, how many models each runs fully in memory, and the estimated speed of each on every "}],"toolCount":6,"toolsHash":"865e2b3c5f01291d76f147918502fb5949c5d5a450ddd8db86d356c2ead0652d","serverName":"readygpu","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}}],"tools":[{"name":"search_models","description":"Find open-weight AI models by name or task (chat, coding, agentic, vision, reasoning). Returns each model's slug, size, context length and licence; use the slug"},{"name":"find_hardware","description":"List graphics cards or complete machines (Macs, mini PCs) sold in a market, with memory, bandwidth, the estimated speed on a model and a link to each one's page"},{"name":"hardware_details","description":"One graphics card or machine in a market: its specifications, which models it runs fully in memory at a context length and how fast, and a link to its page and "},{"name":"hardware_for_model","description":"For one model: how much memory it needs at each context length, and the fastest hardware (and the fastest Mac) that runs it fully in memory in a market, with th"},{"name":"best_hardware","description":"The ranked 'best for local AI' lists of a market (all graphics cards, cards under a price, used cards, Macs and mini PCs): best first by the most capable model "},{"name":"compare_hardware","description":"Two graphics cards or machines side by side in a market: memory, bandwidth, how many models each runs fully in memory, and the estimated speed of each on every "}],"package":null,"toolSurface":{"id":"ts_kmm4hrsmhypk","endpointId":"ep_2tgy98zazy6e","hash":"865e2b3c5f01291d76f147918502fb5949c5d5a450ddd8db86d356c2ead0652d","toolCount":6,"serverName":"readygpu","serverVersion":"1.0.0","protocolVersion":"2025-06-18","firstSeenAt":"2026-10-28T20:27:05.557Z","lastSeenAt":"2026-10-30T09:30:56.781Z","observations":6,"toolNames":["search_models","find_hardware","hardware_details","hardware_for_model","best_hardware","compare_hardware"],"distinctSurfaces":1},"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"mcp_registry","key":"com.readygpu/readygpu","url":"https://registry.modelcontextprotocol.io/v0/servers/com.readygpu%2Freadygpu","firstSeenAt":"2026-10-28T19:18:17.004Z","fetchedAt":"2026-10-28T19:18:17.004Z","normalizedAt":"2026-10-28T19:18:17.004Z"}]},"firstSeenAt":"2026-10-28T19:18:17.004Z","updatedAt":"2026-10-30T09:33:47.725Z"}