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io.github.TheBaronofAI/vetted-consumer

REMOTE · VETTEDCONSUMER.COM · SCANNED AUG 3

Will a local LLM run on your hardware? GGUF quant, buy-vs-rent-vs-API cost, used-GPU prices.

+3 this week 65 Trust /100
Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →

Endpoint Security57
Transport & Reachability100
Schema Quality & AI Usability68
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 1465 tokens (~162/item across 9 items; 9 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
  • Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

remote · vettedconsumer.com

# add to Claude Code
claude mcp add --transport http thebaronofai-vetted-consumer https://vettedconsumer.com/mcp
# ~/.codex/config.toml
[mcp_servers.thebaronofai-vetted-consumer]
url = "https://vettedconsumer.com/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "thebaronofai-vetted-consumer": {
      "type": "remote",
      "url": "https://vettedconsumer.com/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add thebaronofai-vetted-consumer --url https://vettedconsumer.com/mcp --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  thebaronofai-vetted-consumer:
    url: "https://vettedconsumer.com/mcp"
// mcp.json
{
  "mcpServers": {
    "thebaronofai-vetted-consumer": {
      "type": "http",
      "url": "https://vettedconsumer.com/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 2 Aug 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

  • 31 Jul 26 0
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 30 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 28 Jul 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

  • 27 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 26 Jul 26 61

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 3 Aug 2026 · Probed https://vettedconsumer.com/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=vettedconsumer.com CN=WE1,O=Google Trust Services,C=US 11 Jun 2026 9 Sept 2026 ECDSA 256 ECDSA-SHA256 58e95889240d7e6713f8294940bcda49
SANs: vettedconsumer.com, *.vettedconsumer.com
CN=WE1,O=Google Trust Services,C=US (CA) CN=GTS Root R4,O=Google Trust Services LLC,C=US 13 Dec 2023 20 Feb 2029 ECDSA 256 ECDSA-SHA384 7ff31977972c224a76155d13b6d685e3
CN=GTS Root R4,O=Google Trust Services LLC,C=US (CA) CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE 15 Nov 2023 28 Jan 2028 ECDSA 384 SHA256-RSA 7fe530bf331343bedd821610493d8a1b
DNSSEC insecure

Validation of vettedconsumer.com. Not signed

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
com. present 19718 13 Verified
vettedconsumer.com. absent Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200
Header Value
x-content-type-options nosniff
Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://vettedconsumer.com/mcp Verified 200
http (plaintext) http://vettedconsumer.com/mcp HTTPS enforced 301 https://vettedconsumer.com/mcp/
MCP tools — 9 exposed · ~1,465 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens
can_i_run_it ~294

Will a given local LLM run on given hardware? Returns fit, the best quant that fits, theoretical tok/s, and real owner-measured tok/s where available.

NameTypeReqDescription
active_bnumberFor an unlisted model: active params in billions (= total for dense, less for MoE)
bandwidth_gbpsnumberFor custom hardware: memory bandwidth in GB/s
contextnumberContext window in tokens (default 8192)
hardwarestringHardware name/id, e.g. 'rtx-3090', 'Mac 128GB', 'Strix Halo'. Use list_hardware to see known ones.
kv_precisionstringKV cache precision (default f16)
modelstringModel name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names.
mxfp4booleanTrue if the model ships natively in MXFP4 (e.g. gpt-oss)
total_bnumberFor an unlisted model: total parameters in billions
unifiedbooleanTrue for unified-memory machines (Macs, Strix Halo, CPU+RAM)
vram_gbnumberFor custom hardware: VRAM or unified memory in GB

No output schema declared.

No examples provided.

cheapest_hardware_for_model ~165

The cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context.

NameTypeReqDescription
active_bnumberFor an unlisted model: active params in billions (= total for dense, less for MoE)
contextnumberContext window in tokens (default 8192)
modelstringModel name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names.
mxfp4booleanTrue if the model ships natively in MXFP4 (e.g. gpt-oss)
total_bnumberFor an unlisted model: total parameters in billions

No output schema declared.

No examples provided.

compare_hardware ~203

Side-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.

NameTypeReqDescription
active_bnumberFor an unlisted model: active params in billions (= total for dense, less for MoE)
contextnumberContext window in tokens (default 8192)
hardwarestringyes2 to 4 hardware names/ids, comma-separated
kv_precisionstringKV cache precision (default f16)
modelstringModel name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names.
mxfp4booleanTrue if the model ships natively in MXFP4 (e.g. gpt-oss)
total_bnumberFor an unlisted model: total parameters in billions

No output schema declared.

No examples provided.

cost_compare ~204

Buy vs rent vs API cost to run a model locally: monthly/1y/3y totals, break-even months, and the energy cost per 1M tokens. Same math as /cost-calculator/.

NameTypeReqDescription
apinumberAPI $/million tokens (default 1.0)
hardwarestringCatalogued hardware name/id (see list_hardware), e.g. 'rtx-3090-used'
hoursnumberActive hours per day (default 3)
kwhnumberElectricity $/kWh (default 0.16)
price_usdnumberFor custom hardware: price in USD
rentnumberCloud GPU $/hour (default 0.59)
tdp_wnumberFor custom hardware: board power draw in watts
tokensnumberTokens generated per day, for the API comparison (default 300000)

No output schema declared.

No examples provided.

get_used_gpu_prices ~53

Current typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly).

NameTypeReqDescription
gpustringOptional name/id filter, e.g. "3090"

No output schema declared.

No examples provided.

list_hardware ~26

List the machines the tools know about (memory, bandwidth, price, buy link).

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

list_models ~30

List the local LLM model classes the tools know about (params, dense/MoE, native context).

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

recommend_hardware ~196

Ranked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap.

NameTypeReqDescription
active_bnumberFor an unlisted model: active params in billions (= total for dense, less for MoE)
budgetnumberOptional max price in USD
contextnumberContext window in tokens (default 8192)
kv_precisionstringKV cache precision (default f16)
modelstringModel name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names.
mxfp4booleanTrue if the model ships natively in MXFP4 (e.g. gpt-oss)
total_bnumberFor an unlisted model: total parameters in billions

No output schema declared.

No examples provided.

recommend_quant ~294

Which GGUF quantization to download for a model on given hardware: the full quant ladder with file size, max context, and tok/s for each, plus the recommended pick.

NameTypeReqDescription
active_bnumberFor an unlisted model: active params in billions (= total for dense, less for MoE)
bandwidth_gbpsnumberFor custom hardware: memory bandwidth in GB/s
contextnumberContext window in tokens (default 8192)
hardwarestringHardware name/id, e.g. 'rtx-3090', 'Mac 128GB', 'Strix Halo'. Use list_hardware to see known ones.
kv_precisionstringKV cache precision (default f16)
modelstringModel name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names.
mxfp4booleanTrue if the model ships natively in MXFP4 (e.g. gpt-oss)
total_bnumberFor an unlisted model: total parameters in billions
unifiedbooleanTrue for unified-memory machines (Macs, Strix Halo, CPU+RAM)
vram_gbnumberFor custom hardware: VRAM or unified memory in GB

No output schema declared.

No examples provided.