
llm-oracle
io.github.weiseer由 GitHub 帳號 weiseer 發布v0.2.0更新於 Oct 24, 2026
Up-to-date LLM pricing + availability catalog with cited sources for AI agent routing.
概覽
一個本機 MCP 伺服器,為助理提供附引用來源的 LLM 供應商價格與可用性目錄,方便比較模型並依 token 用量找出最便宜的選項。
- 可以做什麼
- 列出模型,可依供應商或能力篩選,並取得單一模型的完整記錄及其來源連結與時間戳。依指定的輸入與輸出 token 數估算成本並排序模型,可要求特定能力。並排比較多個模型,並查詢某個模型目前的可用狀態及其引用來源。本版本目錄涵蓋五家供應商、約十個模型。
- 適用情境
- 適合助理在請求當下需要在多個 LLM 供應商或模型之間做選擇,且需要目前價格而非寫死的表格。也適合查核或引用價格說法的出處,因為每筆記錄都連到供應商官方文件。
- 執行需求
- 以本機程序執行;README 的設定方式使用 Python 並需複製儲存庫,清單中則列出 npm 套件。預設需要連線至託管目錄;設定 LLM_ORACLE_LOCAL_ONLY 可只用內建目錄,設定 LLM_ORACLE_URL 可指向其他目錄。免費額度不需帳號或金鑰。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 llm-oracle,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
llm-oracle
Continuously-updated catalog + query API for LLM provider availability and pricing.
Built by weiseer.
What it does
Given a question like "for this prompt of N input tokens plus M expected output tokens, which currently-available model offers the lowest cost?" the oracle answers in milliseconds, with the source URL it used for the pricing claim.
Use it as:
- an MCP server for AI agents that need to make routing decisions at inference time
- an HTTP JSON API for any tool that wants up-to-date LLM pricing/availability
- a raw
catalog.jsonyou can audit, vendor, or contribute fixes to
Why
LLM pricing changes monthly. Every multi-model app rebuilds the same lookup table. We maintain it so you don't.
- Cited: every pricing row links to the provider's official documentation
- Versioned:
as_oftimestamp on every response so you know how fresh the data is - Open: catalog is public JSON, MIT licensed; client/server code is Apache-2.0
- Cross-checked: source data verified against the open-source LiteLLM price file where overlap exists
Coverage (v0)
5 providers, ~10 models. Growing as we observe demand.
- Anthropic: Claude Opus 4.7, Sonnet 4.6, Haiku 4.5
- OpenAI: GPT-5, GPT-4o
- Google: Gemini 2.5 Pro, Gemini 2.5 Flash
- DeepSeek: Reasoner, Chat
- Mistral: Large
Quickstart
As an MCP server (Claude Desktop, Cursor, Continue, Cline, etc.)
Add to your MCP client config:
The agent now has tools:
list_models(provider?, capability?)→ list models, optionally filteredget_model(model_id)→ full record for one modelfind_cheapest(input_tokens, output_tokens, required_capabilities?)→ ranked by estimated costcompare_models(model_ids[], input_tokens?, output_tokens?)→ side-by-sidecheck_availability(model_id)→ current status with cited source
As an HTTP API
As raw JSON
Pricing
Paid tiers settle in USDC. Email [email protected] to subscribe; we issue an API key and confirm receipt. (We'll automate this when the first three paid customers exist.)
Schema
See catalog.json for the canonical schema. Per-model fields include model_id, provider, family, context_window, max_output_tokens, input_price, output_price, cached_input_price, capabilities, availability_status, source URLs, and timestamps.
Update cadence
- Pricing: daily cron + manual when a price change is publicly announced
- Availability: 5-minute poll of provider status pages where available; daily smoke-test otherwise
Errors and disagreements
Found a stale price? An incorrect capability flag? A missing model? Open an issue — please include the source URL we should be tracking.
Telemetry
The hosted service logs each request as a single event (caller, query summary, latency, paid status) to weiseer's append-only audit ledger. The MCP server you self-host logs nothing.
Building on this
The catalog format is MIT licensed. Vendor it, mirror it, build on top of it. We ask only that you cite weiseer/llm-oracle somewhere visible if you redistribute the data.
The server and MCP code are Apache-2.0.
Roadmap (probe-pulled, not pre-planned)
This is P-001 in weiseer's strategic backlog — a market sensor for organism's architecture v2. We expand it where users ask, kill it if 4 weeks of public availability brings under 100 calls. Don't expect a polished commercial product; expect honest experimentation with daily updates.
What we might add (in observed-demand order):
- More providers (Cohere, xAI, AI21, Together, Replicate hosted, Bedrock, Azure pricing variants)
- x402 micropayments for high-volume agent buyers (deferred — see arXiv 2605.11781 on protocol security)
- Historical pricing time-series
- SLA + uptime aggregates per provider
- Per-region availability where providers vary
- Self-hosted model cost estimators (with caveats)
Contact
來源:README.md,提交 d45f6f1
工具
0版本歷史
1- v0.2.0最新Sep 16, 2026
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