
TokenLab MCP|让 AI 智能体调用模型与多模态工具
TokenLab MCP:对比 LLM 价格,访问 31-80 个多模态工具。
tokenlabai · HN
TokenLab MCP, model discovery, pricing, and native AI endpoint tools
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TokenLab MCP:对比 LLM 价格,访问 31-80 个多模态工具。
tokenlabai · HN
TokenLab MCP, model discovery, pricing, and native AI endpoint tools

追踪100+来源的AI和LLM新闻和模型发布。
jonam21 · HN
KBlip – turns AI/LLM news across 100 sources into daily digest threads

用WebAssembly在浏览器运行和管理LLM模型
userfrom1995 · HN
Goku – WASM (wllama)-powered LLM inference and model manager

追踪目标和失败的LLM智能体,跨会话保存状态并展示每步推理。
u/OGMYT · Reddit
I built LOLM, a lower-cost LLM agent that shows what it actually did — looking for blunt feedback I’m one of the founders/builders behind LOLM. Most AI products show an answer but hide whether the system retrieved anything useful, verified the result, switched models, hit a limit, or simply stopped. LOLM exposes those parts through controller events and run receipts. It includes: - Live agent - CLI - Coding and small app-building workflows - Memory and self-hosting options - Control decis

Convert PDF, DOCX, XLSX, CSV, JSON, XML, HTML, Images to clean Markdown optimized for AI Agents, RAG, and Vector DBs. 100% Privacy-First, In-Browser Conversion.
@13SahajChawla · X
For professionals to redact their client's sensitive informations before giving AI to process it & while converting any kind of document to a structured MD file. Better quality outputs, 100% privacy with on-browser local processing, and fully free!

本地路由LLM提示、减少云API成本的SDK。
u/econobro · Reddit
Built a tool that skips the cloud LLM call when the prompt doesn't need one — would love feedback Live demo, no login, paste anything and see where it actually resolves and why: link What I built Offramp — a small client-side SDK that sits in front of whatever LLM API call your app already makes, and resolves some prompts entirely on-device instead of sending them to Claude/GPT/whatever cloud model you're using. Yes, I used Claude (you'll be able to tell right away if yo

为LLM输出提供token级引文API,通过注意力分析验证。
apoorvumang · HN
TokenPath – token-level citations for LLM output, read from attention

用 LLM 评估 AI agent 对话质量,提供评分卡和成本分析。
@tech_maju · X

扫描AI提示词和端点的漏洞,实时监控生产LLM的安全性和合规。
@CognisafeUK · X

检测LLM API是否被降智或偷换模型,一键跑6项探针得出结果
cocodot LLM 降智检测 — 免费的 LLM API「降智/偷换模型」在线检测:填入任意 OpenAI 兼容端点的 base_url 和临时 API Key,跑 6 项探针(模型声明、动态题、能力完整性等)生成分项报告;Key 仅用于当次检测、不落库不留存,检测方法[开源](https://github.com/cocodot2026/cocodot-llmprobe)

Ornymo通过语义缓存减少LLM查询成本和延迟。
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]

用比特币或门罗币购买 API 密钥访问 Anthropic 和 OpenAI,无需账户。
not_wowinter13 · HN
Anonymous LLM proxy. Pay in crypto, no account needed