About apipriceindex
apipriceindex is an MCP server for AI agents that need current, source-linked LLM API pricing and deal data. It supports model search, cost estimates, comparisons, and price history, while marking verification dates and confidence rather than silently supplying unknown prices.
Key features
- 01Search models by provider, price, and capabilities
- 02Retrieve verified prices with sources and dates
- 03Estimate and rank monthly workload costs
- 04Find free models, discounts, and credits
- 05Compare models, hosts, and offers
- 06Track price changes and capability levels
Use cases
- 01Find models currently free to call
- 02Estimate monthly API costs across models
- 03Compare prices and hosting options
- 04Review recent price rises and drops
MCP support
Exposes pricing, model search, estimate, comparison, deal, and price-history tools to MCP clients. Data is fetched live from the index and unavailable or untracked prices are reported rather than invented.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
3Saved tool list · updated 4d ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| query | string | Yes | |
| provider | any | No | |
| min_context | any | No | |
| open_weights | any | No |
Details
From the project READMEapipriceindex-mcp
An MCP server that gives any AI agent live, verified LLM API prices — and today's deals.
Ask your assistant "which LLMs are free to call right now?", "what's the
cheapest model at least as good as GPT-5.6 Sol?" or "what would 200M input /
15M output tokens a month cost me on Sonnet vs GPT?" and it answers from
today's index — every price with its verification date, cross-check confidence
and source URL. Data from apipriceindex.com
(CC BY 4.0, re-checked daily from each provider's own price list or from
OpenRouter's per-provider data; every price names its source in source_url).
Tools
| Tool | What it does |
|---|---|
search_models | Find model ids by name/provider; filter by context window, open weights, max price (input + output), capabilities (tools, reasoning, vision, json) and min speed |
get_price | Verified price of one model: input/output/cached input USD per Mtok, verified_at, confidence, source; speed, availability and Epoch score when known; for open-weight models, the weights precision, context and max output the host serves, each with its state, source and date |
estimate_cost | Monthly bill of a workload; ranks chosen models — or the whole catalog — cheapest first |
list_deals | Models free to call right now, discounts, free credits and free tiers — each with its end date and official source; filter "ends within N days" |
offers_table | Every host serving one model, with the columns you choose (input, output, cache, discount, speed, first token, uptime, precision, context, max output, verified_at) |
compare_models | Two to four models side by side: lowest prices and who gives them, providers, fastest host, context, license, Epoch score, monthly cost |
cheapest_at_level | Cheapest models reaching an Epoch Capabilities Index score — or as good as a model you name |
price_changes | Price drops and rises over the last N days, and the models released in that time |
Install
pip install apipriceindex-mcp
Claude Code / Claude Desktop:
claude mcp add apipriceindex -- apipriceindex-mcp
Or in any MCP client config:
{ "mcpServers": { "apipriceindex": { "command": "apipriceindex-mcp" } } }
Behavior
- Data is fetched live from the index (15-minute in-memory cache) — never stale training data.
- Index unreachable → explicit error. No cached or invented price is ever served silently.
- Index older than 14 days → answers still come, with a warning pointing at the index's health endpoint.
- Model not tracked → says so, links the dataset. No price invented.
- Cache discount only where the provider publishes a cached-input price.
- Deals always carry an end date —
no end datewhen the host publishes none — and the link to the host's own page. - Speed and availability are read from OpenRouter and always come with their window (median over 30 minutes, share of successful requests over 24 hours). No tail latency or error rates.
- What a host serves (weights precision, context, max output) is read at
the host's own catalogue or docs where its terms allow, otherwise as the
host declares to OpenRouter. Each value carries its state:
published,not_stated(the host's source does not state it),not_read(the host's terms forbid automatic reading and OpenRouter has no value) orto_check. Nothing is guessed. - One third-party score: the Epoch Capabilities Index by Epoch AI (CC BY 4.0). Every answer that carries it carries its credit. Otherwise, cost only: the index does not rank model quality.
Environment: APIPRICEINDEX_URL overrides the dataset URL (testing);
deals.json and pricing-history.csv are read next to it.
Changelog
- 0.3.0 — What each host serves of an open-weight model:
get_pricereturnsserved.precision,served.contextandserved.max_output, each with its state, source and date, and the maker's values inserved.maker;offers_tabletakesprecisionandmax_outputcolumns, and an empty served cell comes with<column>_state. Other answers unchanged. - 0.2.1 —
get_priceand this README now say where prices are read: each provider's own price list, or OpenRouter's per-provider data, named bysource_url. They said "official pricing pages", which was true of about one price in four. No change to the tools or their answers. - 0.2.0 —
list_deals,offers_table,compare_models,cheapest_at_level,price_changes;search_modelsfilters by max price, capabilities and min speed; Epoch score, speed and availability where known. The three 0.1 tools answer as before. - 0.1.1 —
search_models,get_price,estimate_cost.
License
Code: MIT. Price data: CC BY 4.0, attribution "API Price Index". Epoch Capabilities Index: CC BY 4.0, credit Epoch AI.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.