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first catalogued 2026-10-14;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
whichmodel-mcp
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
> A model routing advisor for autonomous agents — get cost-optimised LLM recommendations via MCP.
**whichmodel.dev** tracks pricing and capabilities across 100+ LLM models, updated every 4 hours. This MCP server exposes that data so AI agents can pick the right model at the best price for every task.
MCP Endpoint
**Transport:** Streamable HTTP (MCP spec 2025-03-26)
Quick Start
Add to your MCP client config:
No API key required. No installation needed.
Stdio (local clients)
For MCP clients that use stdio transport (Claude Desktop, Cursor, etc.):
This runs a thin local proxy that forwards requests to the remote server.
Tools
recommend_model
Get a cost-optimised model recommendation for a specific task type, complexity, and budget.
| Parameter | Type | Description |
|-----------|------|-------------|
| task_type | enum (required) | chat, code_generation, code_review, summarisation, translation, data_extraction, tool_calling, creative_writing, research, classification, embedding, vision, reasoning |
| complexity | low \| medium \| high | Task complexity (default: medium) |
| estimated_input_tokens | number | Expected input size in tokens |
| estimated_output_tokens | number | Expected output size in tokens |
| budget_per_call | number | Maximum spend in USD per call |
| requirements | object | Capability requirements: tool_calling, json_output, streaming, context_window_min, providers_include, providers_exclude |
Returns: recommended model, alternative, budget option, cost estimate, and reasoning.
---
compare_models
Head-to-head comparison of 2–5 models with optional volume cost projections.
| Parameter | Type | Description |
|-----------|------|-------------|
| models | string[] (required) | Model IDs, e.g. [anthropic/claude-sonnet-4, openai/gpt-4.1] |
| task_type | enum | Context for comparison |
| volume | object | calls_per_day, avg_input_tokens, avg_output_tokens for daily/monthly cost projections |
Returns: pricing, capabilities, quality tiers, and projected costs per model.
---
get_pricing
Raw pricing data lookup with filters by model, provider, price ceiling, and capabilities.
| Parameter | Type | Description |
|-----------|------|-------------|
| model_id | string | Specific model ID |
| provider | string | Filter by provider, e.g. anthropic |
| max_input_price | number | Max input price per million tokens (USD) |
| capabilities | string[] | Required capabilities: tool_calling, json_output, streaming, vision |
| min_context_window | number | Minimum context window in tokens |
| limit | number | Max results (1–100, default 20) |
---
check_price_changes
See what model pricing has changed since a given date.
| Parameter | Type | Description |
|-----------|------|-------------|
| since | string (required) | ISO date, e.g. 2026-04-01 |
| model_id | string | Filter to a specific model |
| provider | string | Filter to a specific provider |
Returns: price increases, decreases, new models, and deprecations.