Server definition

Hash: sha256:330789a0a733fd95daac9507a003152a10a06f6d810bcd8d9273347f5183d3ec
What it is: What a remote MCP server returned when asked what it offers: 3 tools

The blob, as servednamed by its sha256

{
  "instructions": null,
  "tools": [
    {
      "description": "Check whether a specific local LLM fits in the memory of a specific GPU or Apple Silicon Mac. Returns fits/tight/won't-fit verdict with the memory breakdown (weights, KV cache, linear-attention state when present, runtime overhead, reserve), max context, and a concrete fix if it doesn't fit. Use this whenever a user asks anything like \"can I run <model> on my <GPU/Mac>?\", \"will <model> fit in <N>GB?\", or \"what do I need to run <model>?\". Estimates using curated, config-derived architecture fields (MLA, sliding-window, hybrid attention, MoE modeled).",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "context_tokens": {
            "description": "Context length in tokens (default 8192). Alias: ctx (same field as the REST API).",
            "minimum": 1024,
            "type": "integer"
          },
          "ctx": {
            "description": "Alias of context_tokens — accepted because the REST API uses this name. Do not pass both with different values.",
            "minimum": 1024,
            "type": "integer"
          },
          "gpu": {
            "description": "GPU name, fuzzy — e.g. \"RTX 4090\", \"RX 7900 XTX\", \"A100 80GB\". Multi-GPU rigs: join with + — e.g. \"RTX 5090 + RTX 3090\" (VRAM pools across cards). Provide gpu OR mac_ram_gb.",
            "type": "string"
          },
          "gpu_count": {
            "description": "Number of identical copies of the gpu (e.g. gpu=\"RTX 3090\", gpu_count=2 for a 2×3090 rig). Default 1.",
            "maximum": 8,
            "minimum": 1,
            "type": "integer"
          },
          "kv_bits": {
            "description": "KV-cache quantization bits (default 16 = F16)",
            "enum": [
              16,
              8,
              4
            ],
            "type": "number"
          },
          "mac_ram_gb": {
            "description": "Apple Silicon unified memory in GB — e.g. 16, 64, 512. Provide gpu OR mac_ram_gb.",
            "maximum": 2048,
            "minimum": 8,
            "type": "integer"
          },
          "model": {
            "description": "LLM name, fuzzy — e.g. \"GLM-4.7-Flash\", \"gpt-oss-20b\", \"gemma 31b\"",
            "type": "string"
          },
          "quant": {
            "description": "Weight quantization. GPU: Q4_K_M(default)/Q5_K_M/Q6_K/Q8_0/FP16. Mac: 4/8(default)/16 (bits).",
            "type": "string"
          }
        },
        "required": [
          "model"
        ],
        "type": "object"
      },
      "name": "check_llm_fit",
      "outputSchema": null
    },
    {
      "description": "List the built-in model names and hardware names this fit-checker knows (for mapping user wording to exact names). Standard text-only HuggingFace transformer configs can also be checked via fitllm.run; unsupported architectures are rejected.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "list_supported",
      "outputSchema": null
    },
    {
      "description": "Rank which popular local LLMs fit on a given GPU or Apple Silicon Mac (at ~4-bit quantization, 8K context) — models that fit come first, biggest first, with max context each. Use when a user asks \"what can I run on my <GPU/Mac/N GB>?\", \"best local model for my machine?\", or gives hardware without naming a model.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "gpu": {
            "description": "GPU name, fuzzy. Multi-GPU rigs: join with + (e.g. \"RTX 5090 + RTX 3090\"). Provide gpu OR mac_ram_gb.",
            "type": "string"
          },
          "gpu_count": {
            "description": "Number of identical copies of the gpu. Default 1.",
            "maximum": 8,
            "minimum": 1,
            "type": "integer"
          },
          "mac_ram_gb": {
            "description": "Apple Silicon unified memory GB. Provide gpu OR mac_ram_gb.",
            "maximum": 2048,
            "minimum": 8,
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "what_fits_on_hardware",
      "outputSchema": null
    }
  ]
}

Verify it yourself

curl -s https://api.teppi.xyz/v1/evidence/sha256:330789a0a733fd95daac9507a003152a10a06f6d810bcd8d9273347f5183d3ec | sha256sum