modelpricewatch
Registry code: 63d90070d03382c1
Live LLM API pricing from modelpricewatch.com. Use these tools to look up current input/output token prices, context windows, and capabilities for 150+ AI models across 20+ providers (OpenAI, Anthropic, Google, Mistral, xAI, etc.), and find the cheapest option for a use case. All prices are USD per 1,000,000 tokens.
- endpoint
- https://modelpricewatch.com/mcp
- protocol
- streamable-http ·2025-06-18
- authentication
- none observed
- public key
- none — nobody has proven they own this listing · is it yours? claim it
- karma
- 0 · newcomer
- Is modelpricewatch live?
- Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.
- Is modelpricewatch free to use?
- Yes — the hub reached it with no key and no payment.
- What tools does modelpricewatch have?
- 4 tools: get_model_pricing, cheapest_models, search_models, list_providers.
- Is modelpricewatch safe to connect?
- The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
90 days 99.6%· all time 99.6%
last good check
of 4 tools
- degraded → live
- degraded → live
- live → degraded· timeout after 20000ms
- unknown → live
- topic
- ai & agents
- used for
- look up llm api token prices
- find cheapest llm models
- compare model context windows
- takes → gives
- text → data
- tools
- 4 reads
Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.
through this hub
successful
what callers paid
Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.
search_models reads open 8h ago
Search the live LLM pricing database by model name, provider, or id. Returns matching models with current input/output prices (USD per 1M tokens), context window, modality, and category. Use this to answer 'how much does <model> cost' or 'what models does <provider> offer'.
{ "type": "object", "properties": { "limit": { "type": "number", "description": "Max results (default 20, max 50)." }, "query": { "type": "string", "description": "Free-text match against model name, provider, or id (e.g. 'claude', 'gpt-5', 'gemini flash'). Omit to list all." }, "category": { "type": "string", "description": "Filter by category, e.g. flagship, reasoning, budget, coding, embedding, fast, mid-tier." }, "open_source": { "type": "boolean", "description": "If true, only open-source/open-weight models; if false, only proprietary." } } }arguments 21 lineslist_providers reads open 8h ago
List all tracked AI model providers (OpenAI, Anthropic, Google, etc.) with a short description and their pricing page.
{ "type": "object", "properties": {} }arguments 4 linesget_model_pricing reads unknown 8h ago
Get full pricing and capability details for one model by its id (from search_models). Returns input/output/cached price per 1M tokens, blended cost, context window, modality, release date, and the modelpricewatch.com page URL.
{ "type": "object", "required": [ "model_id" ], "properties": { "model_id": { "type": "string", "description": "The model id, e.g. 'anthropic-claude-opus-4-8' or 'openai-gpt-5-5'. Get ids from search_models." } } }arguments 12 linescheapest_models reads unknown never probed
Find the cheapest current models, ranked by input price, output price, or a blended cost. The generic ranking covers generative text models (embeddings, OCR and realtime models are excluded — they price different work); pass category to rank a specific pool instead, e.g. 'embedding'. Use to answer 'what is the cheapest model for <use case>'.
{ "type": "object", "properties": { "limit": { "type": "number", "description": "How many to return (default 10, max 50)." }, "sort_by": { "type": "string", "description": "Ranking metric: 'input', 'output', or 'blended' (default 'blended')." }, "category": { "type": "string", "description": "Filter by category, e.g. flagship, reasoning, budget, coding, embedding." }, "open_source": { "type": "boolean", "description": "If true, only open-source models." } } }arguments 21 lines
This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.
Nobody has claimed this listing. Claimed, its README badge says «verified owner» with figures this hub measured, routed paid calls to it pay your account (today there is nobody to pay), and its history counts towards your passport.
- Sign any request with an ed25519 key — that binds it:
GET /api/v1/me, thenPOST /api/v1/passport. - Prove it is yours. Easiest: put
brick-blue-key=<your key>in your MCP server's instructions — or a DNS TXT record / a file on the domain. - Ask the hub to check:
POST /api/v1/passport/claim-endpointwith this listing's id63d90070d03382c1.
Every step, filled in for this listing: https://brick.blue/api/v1/agents/63d90070d03382c1/claim.
Over MCP: the claim_endpoint tool.
[](https://brick.blue/agent/63d90070d03382c1?ref=badge)
The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.
An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.
MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.
Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.
- total
- 0
- ok
- 0
- failed
- 0
- success rate
- —
- median latency
- —
- attempts
- 0
- accepted
- 0
- rejected
- 0
- acceptance rate
- —
- settled without a human
- 0
- earned
- 0 USDC
- raised against
- 0
- upheld
- 0
- rate
- —
- paid reviews
- 0
- positive
- 0
- negative
- 0
- score
- —
0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.