# io.github.Daichi-Kudo/llm-advisor (npm · llm-advisor-mcp)

Real-time LLM/VLM benchmarks, pricing, and recommendations. 300+ models, 5 sources.

- Trust score: 66/100 (medium)
- Change this week: +20
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- npm · `llm-advisor-mcp`: 66/100 (this document), [markdown](https://verifymcp.io/servers/daichi-kudo-llm-advisor/llm-advisor-mcp.md), [page](https://verifymcp.io/servers/daichi-kudo-llm-advisor/llm-advisor-mcp)

## Channel facts

- Registry: `npm`
- Package: `llm-advisor-mcp`
- Version: `0.4.5`
- Transport: `stdio`

## Trust breakdown

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. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Supply Chain Security**: 87/100
  - No malware found by supply-chain analysis.
  - Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 46 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 77/100
  - AI-judged instruction clarity (excellent).
  - Tool/resource definitions use about 467 tokens (~116/item across 4 items; 4 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 0/100
  - Stability not yet verified: not enough scan history yet (needs a 30-day window).
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

**Unverified: 1 category.** A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

## Install

### Claude

```bash
claude mcp add daichi-kudo-llm-advisor -- npx -y llm-advisor-mcp
```

### Codex

```bash
codex mcp add daichi-kudo-llm-advisor -- npx -y llm-advisor-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "daichi-kudo-llm-advisor": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "llm-advisor-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add daichi-kudo-llm-advisor --command npx --arg -y --arg llm-advisor-mcp
```

### Hermes

```yaml
mcp_servers:
  daichi-kudo-llm-advisor:
    command: "npx"
    args: ["-y", "llm-advisor-mcp"]
```

### Other

```json
{
  "mcpServers": {
    "daichi-kudo-llm-advisor": {
      "command": "npx",
      "args": [
        "-y",
        "llm-advisor-mcp"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-02 (score 66, +61)

- [security regression] Provenance: unverified → fail
- [security improvement] Known CVEs: unverified → partial
- [security improvement] Install scripts: unverified → pass
- [security improvement] Malware scan: unverified → pass
- [security] Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window).
- [functional improvement] Schema quality: unverified → excellent
- [functional improvement] License: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] MCP protocol: unverified → pass
- [functional improvement] Tool coverage: unverified → 100
- [functional] Licence: MIT

### 2026-08-01 (score 5, −16)

- [functional regression] Tool coverage: 100 → unverified
- [functional] First check of Schema quality: unverified

### 2026-07-31 (score 21, −25)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-27 (score 46)

First indexed and scored.

## MCP tools (4)

### `get_model_info` (~117 tokens)

Get detailed information about a specific LLM/VLM model: pricing, benchmarks, capabilities, and ready-to-use API code example. Returns structured Markdown (~300 tokens).

Input parameters:

- `api_format` (string): API example format (default: openai_sdk)
- `include_api_example` (boolean): Include API usage code example (default: true)
- `model` (string, required): Model ID or partial name (e.g., "anthropic/claude-sonnet-4.6", "gpt-5.1", "gemini")

### `list_top_models` (~116 tokens)

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).

Input parameters:

- `category` (string, required): 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

### `compare_models` (~78 tokens)

Compare 2-5 LLM/VLM models side-by-side: pricing, benchmarks, capabilities. Returns a compact Markdown comparison table (~400 tokens).

Input parameters:

- `models` (array, required): Model IDs or partial names (e.g., ["claude-sonnet-4.6", "gpt-5.2", "gemini-3-pro"])

### `recommend_model` (~156 tokens)

Get personalized model recommendations based on use case, budget, and requirements. Returns top 3 picks with reasoning (~350 tokens).

Input parameters:

- `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, required): Primary use case

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/daichi-kudo-llm-advisor/llm-advisor-mcp#diagnostics

## Score history

- 2026-08-03: 66
- 2026-08-02: 66
- 2026-08-01: 5
- 2026-07-31: 21
- 2026-07-30: 46
- 2026-07-28: 46
- 2026-07-27: 46

## Links

- npm package: https://www.npmjs.com/package/llm-advisor-mcp
- Socket report: https://socket.dev/npm/package/llm-advisor-mcp
- Repository: https://github.com/Daichi-Kudo/llm-advisor-mcp
- Changelog RSS feed: https://verifymcp.io/servers/daichi-kudo-llm-advisor/llm-advisor-mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/daichi-kudo-llm-advisor/llm-advisor-mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/daichi-kudo-llm-advisor/llm-advisor-mcp