tap — alternative #1 to decompose
📇 🏠 🍎 🪟 🐧 - MCP server that compiles AI browser automation into deterministic .tap.json plans (25-op closed union, zero runtime LLM), runs o...
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Recorded alternatives
Every candidate below sits in AI. What ends up on this page is decided entirely by a recorded score — not by bidding, not by editor taste. Review both records, check current vendor terms, then decide.
📇 🏠 🍎 🪟 🐧 - MCP server that compiles AI browser automation into deterministic .tap.json plans (25-op closed union, zero runtime LLM), runs o...
🏎️ ☁️ 🏠 🍎 🪟 🐧 - Synthetic monitoring for LLM inference endpoints. Measure TTFT, latency, throughput, and errors across OpenAI, Anthropic, Go...
📇 🏠 - Track LLM token costs across Claude, GPT and Gemini. MCP server + CLI with optimization hints and $ savings estimates. 📇🏠
🐍 🏠 - این سرور به LLMها امکان استفاده از ماشین حساب را برای محاسبات عددی دقیق میدهد
🍎 🪟 🐧 ☁️ 🏠 🐍 - Magg: یک سرور متا-MCP که به عنوان یک هاب جهانی عمل میکند و به LLMها اجازه میدهد تا به طور خودکار چندین سرور MCP را کشف، نصب...
📇 ☁️ — یک سرور MCP که از دریافت دادهها از یک پایگاه داده با استفاده از کوئریهای زبان طبیعی، با قدرت XiyanSQL به عنوان LLM تبدیل متن به SQL...
Each candidate is a live catalogue record in the same primary category, picked by a deterministic score that Oryxen records in its catalogue: how many meaningful words the two listings share, whether their pricing classes oppose (a paid product against a free one), whether both are open source, and whether either record is featured. The same catalogue state always produces the same list — no randomness, no manual ranking.
No. Rows are ordered only by the recorded score, highest first, with alphabetical ties — payment never influences the order, nothing here is paid placement, and Oryxen charges no listing or placement fee.
Always verify current terms with decompose directly — Oryxen records pricing classes, not live quotes.