io.github.TheBaronofAI/vetted-consumer
REMOTE · VETTEDCONSUMER.COM
Will a local LLM run on your hardware? GGUF quant, buy-vs-rent-vs-API cost, used-GPU prices.
Available components
Last scanned (13 hours ago)
Scores higher than 69% of remote servers
Reachable. Last reached 5 Nov 2026.
Category AI and Machine Learning
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 → Why this is hard to score →
Endpoint Security57
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- Authorisation not fully verified: no authorisation is required to call this server, and 9 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe. See how to fix → View diagnostics → Unverified
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- HSTS check failed: the Strict-Transport-Security header is absent. See how to fix → View diagnostics → Fail
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Transport & Reachability100
- Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass
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 Management100
- No destabilizing schema changes in the last 30 days.Pass
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
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 9 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 9 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Checks we ran (12)
- TLS certificate
- HTTPS
- HSTS header
- DNSSEC
- Transport
- Schema quality
- Stability
- Tool coverage
- Injection markers
- Destructive annotations
- Judged manipulation
- MCP protocol
Checks we could not complete (1)
These are gaps on our side, not findings about this hosted endpoint. We only credit what we can confirm, so a category made up entirely of them scores 0.
- Authorization in Endpoint SecurityAuthorisation not fully verified: no authorisation is required to call this server, and 9 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
Does not apply to this hosted endpoint (2)
- Supply Chain SecurityScored on package channels only. This is a hosted endpoint, so there is nothing to install or inspect.
- Provenance & TransparencyScored on package channels only. This is a hosted endpoint, so there is nothing to install or inspect.
The score does not measure everything. What the score does not measure →
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.
- 28 Sept 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
- 25 Sept 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
- 26 Aug 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
- 25 Aug 26 0
- Stability: 0.97 → pass security
- 11 Aug 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
- 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 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 27 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
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 5 Nov 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 | 7 Oct 2026 | 5 Jan 2027 | ECDSA 256 | ECDSA-SHA256 | 1db0c605d09fe0640e18ed063294ab60 |
| 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 |
Background: What to check on a remote MCP endpoint →
DNSSEC insecure
Validation of vettedconsumer.com. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | Trust anchor | 20326, 38696 | 8, 8 | Verified |
| com. | DS published | 19718 | 13 | Verified |
| vettedconsumer.com. | No DS | 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 |
Background: How OAuth 2.1 works in the 2026 MCP spec →
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/ |
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. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
can_i_run_it 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.
| Name | Type | Req | Description |
|---|---|---|---|
| active_b | number | – | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| bandwidth_gbps | number | – | For custom hardware: memory bandwidth in GB/s |
| context | number | – | Context window in tokens (default 8192) |
| hardware | string | – | Hardware name/id, e.g. 'rtx-3090', 'Mac 128GB', 'Strix Halo'. Use list_hardware to see known ones. |
| kv_precision | string | – | KV cache precision (default f16) |
| model | string | – | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| mxfp4 | boolean | – | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| total_b | number | – | For an unlisted model: total parameters in billions |
| unified | boolean | – | True for unified-memory machines (Macs, Strix Halo, CPU+RAM) |
| vram_gb | number | – | For custom hardware: VRAM or unified memory in GB |
No output schema declared.
No examples provided.
cheapest_hardware_for_model Cheapest hardware for a model ~165
The cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context.
| Name | Type | Req | Description |
|---|---|---|---|
| active_b | number | – | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| context | number | – | Context window in tokens (default 8192) |
| model | string | – | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| mxfp4 | boolean | – | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| total_b | number | – | For an unlisted model: total parameters in billions |
No output schema declared.
No examples provided.
compare_hardware Compare hardware ~203
Side-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.
| Name | Type | Req | Description |
|---|---|---|---|
| active_b | number | – | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| context | number | – | Context window in tokens (default 8192) |
| hardware | string | yes | 2 to 4 hardware names/ids, comma-separated |
| kv_precision | string | – | KV cache precision (default f16) |
| model | string | – | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| mxfp4 | boolean | – | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| total_b | number | – | For an unlisted model: total parameters in billions |
No output schema declared.
No examples provided.
cost_compare Cost: buy vs rent vs API ~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/.
| Name | Type | Req | Description |
|---|---|---|---|
| api | number | – | API $/million tokens (default 1.0) |
| hardware | string | – | Catalogued hardware name/id (see list_hardware), e.g. 'rtx-3090-used' |
| hours | number | – | Active hours per day (default 3) |
| kwh | number | – | Electricity $/kWh (default 0.16) |
| price_usd | number | – | For custom hardware: price in USD |
| rent | number | – | Cloud GPU $/hour (default 0.59) |
| tdp_w | number | – | For custom hardware: board power draw in watts |
| tokens | number | – | Tokens generated per day, for the API comparison (default 300000) |
No output schema declared.
No examples provided.
get_used_gpu_prices Used GPU prices ~53
Current typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly).
| Name | Type | Req | Description |
|---|---|---|---|
| gpu | string | – | Optional name/id filter, e.g. "3090" |
No output schema declared.
No examples provided.
list_hardware 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 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 Recommend hardware ~196
Ranked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap.
| Name | Type | Req | Description |
|---|---|---|---|
| active_b | number | – | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| budget | number | – | Optional max price in USD |
| context | number | – | Context window in tokens (default 8192) |
| kv_precision | string | – | KV cache precision (default f16) |
| model | string | – | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| mxfp4 | boolean | – | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| total_b | number | – | For an unlisted model: total parameters in billions |
No output schema declared.
No examples provided.
recommend_quant Recommend a 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.
| Name | Type | Req | Description |
|---|---|---|---|
| active_b | number | – | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| bandwidth_gbps | number | – | For custom hardware: memory bandwidth in GB/s |
| context | number | – | Context window in tokens (default 8192) |
| hardware | string | – | Hardware name/id, e.g. 'rtx-3090', 'Mac 128GB', 'Strix Halo'. Use list_hardware to see known ones. |
| kv_precision | string | – | KV cache precision (default f16) |
| model | string | – | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| mxfp4 | boolean | – | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| total_b | number | – | For an unlisted model: total parameters in billions |
| unified | boolean | – | True for unified-memory machines (Macs, Strix Halo, CPU+RAM) |
| vram_gb | number | – | For custom hardware: VRAM or unified memory in GB |
No output schema declared.
No examples provided.
How do I install the io.github.TheBaronofAI/vetted-consumer MCP server?
io.github.TheBaronofAI/vetted-consumer is a hosted endpoint at https://vettedconsumer.com/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
remote · vettedconsumer.com
claude mcp add --transport http thebaronofai-vetted-consumer 'https://vettedconsumer.com/mcp'
What is the io.github.TheBaronofAI/vetted-consumer MCP server?
io.github.TheBaronofAI/vetted-consumer is an MCP server listed in the public MCP registry as io.github.TheBaronofAI/vetted-consumer. Will a local LLM run on your hardware? GGUF quant, buy-vs-rent-vs-API cost, used-GPU prices. This page covers its hosted endpoint (https://vettedconsumer.com/mcp).
Is the io.github.TheBaronofAI/vetted-consumer MCP server safe to use?
io.github.TheBaronofAI/vetted-consumer scores 77 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.TheBaronofAI/vetted-consumer MCP server expose?
io.github.TheBaronofAI/vetted-consumer exposes 9 tools: can_i_run_it, recommend_quant, cheapest_hardware_for_model, list_models, list_hardware, and 4 more. Their descriptions and schemas cost roughly 1,465 tokens of context every time the server is loaded.
Does the io.github.TheBaronofAI/vetted-consumer MCP server require authentication?
No. We connected to io.github.TheBaronofAI/vetted-consumer without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.
Is the io.github.TheBaronofAI/vetted-consumer MCP server still maintained?
io.github.TheBaronofAI/vetted-consumer is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What did VerifyMCP test on the io.github.TheBaronofAI/vetted-consumer MCP server?
VerifyMCP ran 12 checks on io.github.TheBaronofAI/vetted-consumer, covering TLS certificate, HTTPS, HSTS header, DNSSEC and 8 more. One item could not be completed, a gap on our side rather than a finding about io.github.TheBaronofAI/vetted-consumer: Authorization. Supply Chain Security and Provenance & Transparency do not apply to a hosted endpoint, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.