io.github.Daichi-Kudo/llm-advisor
NPM · LLM-ADVISOR-MCP · SCANNED AUG 4
Real-time LLM/VLM benchmarks, pricing, and recommendations. 300+ models, 5 sources.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score →
Supply Chain Security83
- No malware found by supply-chain analysis.Pass
- CVE check failed: a known medium-severity CVE affects hono 4.12.33, reached via @modelcontextprotocol/sdk > hono. A fixed version is available. View diagnostics → Fail
- No install/post-install scripts declared.Pass
- Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree. View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 47 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability77
- AI-judged instruction clarity (excellent).Pass
- Tool/resource definitions use about 467 tokens (~116/item across 4 items; 4 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management30
- Stability observed for 9 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
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.
npm · llm-advisor-mcp
claude mcp add daichi-kudo-llm-advisor -- npx -y llm-advisor-mcp
codex mcp add daichi-kudo-llm-advisor -- npx -y llm-advisor-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"daichi-kudo-llm-advisor": {
"type": "local",
"command": [
"npx",
"-y",
"llm-advisor-mcp"
],
"enabled": true
}
}
} openclaw mcp add daichi-kudo-llm-advisor --command npx --arg -y --arg llm-advisor-mcp
mcp_servers:
daichi-kudo-llm-advisor:
command: "npx"
args: ["-y", "llm-advisor-mcp"] {
"mcpServers": {
"daichi-kudo-llm-advisor": {
"command": "npx",
"args": [
"-y",
"llm-advisor-mcp"
]
}
}
} 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.
- 4 Aug 26 +3
- CVE-2026-69207 affects this package: medium ▼ security
- Known CVEs: partial → fail ▼ security
- Stability: unverified → 0.30 ▲ functional
- 2 Aug 26 +61
- Provenance: unverified → fail ▼ security
- Known CVEs: unverified → partial ▲ security
- Install scripts: unverified → pass ▲ security
- Malware scan: unverified → pass ▲ security
- Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window). security
- Schema quality: unverified → excellent ▲ functional
- License: unverified → pass ▲ functional
- Dependency health: unverified → partial ▲ functional
- Maintenance: unverified → pass ▲ functional
- MCP protocol: unverified → pass ▲ functional
- Tool coverage: unverified → 100 ▲ functional
- Licence: MIT functional
- 1 Aug 26 −16
- Tool coverage: 100 → unverified ▼ functional
- First check of Schema quality: unverified functional
- 31 Jul 26 −25
- 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 46
First indexed and scored.
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 4 Aug 2026 · Analysed npm/[email protected]
Provenance none
Ecosystem: npm · Outcome: none
Vulnerabilities 1 finding
| ID | CVE | Severity | Vector | Fix available |
|---|---|---|---|---|
| GHSA-8j4g-w8fx-2239 | CVE-2026-69207 | medium | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L | yes |
Dependencies 95 packages
95 packages in the resolved dependency tree · 95 deprecated · 29 stale.
The dependency tree was only partially resolved, so these counts may be incomplete.
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.
compare_models ~78
Compare 2-5 LLM/VLM models side-by-side: pricing, benchmarks, capabilities. Returns a compact Markdown comparison table (~400 tokens).
| Name | Type | Req | Description |
|---|---|---|---|
| models | array | yes | Model IDs or partial names (e.g., ["claude-sonnet-4.6", "gpt-5.2", "gemini-3-pro"]) |
No output schema declared.
No examples provided.
get_model_info ~117
Get detailed information about a specific LLM/VLM model: pricing, benchmarks, capabilities, and ready-to-use API code example. Returns structured Markdown (~300 tokens).
| Name | Type | Req | Description |
|---|---|---|---|
| api_format | string | — | API example format (default: openai_sdk) |
| include_api_example | boolean | — | Include API usage code example (default: true) |
| model | string | yes | Model ID or partial name (e.g., "anthropic/claude-sonnet-4.6", "gpt-5.1", "gemini") |
No output schema declared.
No examples provided.
list_top_models ~116
List top-ranked LLM/VLM models for a category. Categories: coding, math, vision, general, cost-effective, open-source, speed, context-window, reasoning. Returns a compact Markdown table (~250 tokens).
| Name | Type | Req | Description |
|---|---|---|---|
| category | string | yes | Category to rank models by |
| limit | number | — | Number of models to return (default: 10) |
| min_context | number | — | Minimum context window in tokens |
| min_release_date | string | — | Minimum release date (YYYY-MM-DD). Excludes older models |
No output schema declared.
No examples provided.
recommend_model ~156
Get personalized model recommendations based on use case, budget, and requirements. Returns top 3 picks with reasoning (~350 tokens).
| Name | Type | Req | Description |
|---|---|---|---|
| max_input_price | number | — | Max input price in USD per 1M tokens |
| max_output_price | number | — | Max output price in USD per 1M tokens |
| min_context | number | — | Minimum context window in tokens |
| min_release_date | string | — | Minimum release date (YYYY-MM-DD). Excludes older models |
| require_open_source | boolean | — | Require open-source license |
| require_tools | boolean | — | Require function/tool calling support |
| require_vision | boolean | — | Require vision/image input support |
| use_case | string | yes | Primary use case |
No output schema declared.
No examples provided.