Medama Analytics llms.txt · AI Docs Browser · mdream [llms.txt Tools](https://mdream.dev/llms-txt/medama-analytics/llms-txt) # Medama Analytics llms.txt oss.medama.io/llms.txt [Raw llms.txt](https://oss.medama.io/llms.txt) [Raw llms-full.txt](https://oss.medama.io/llms-full.txt) Copy Markdown [](https://oss.medama.io/llms.txt) llms.txt Docs Session Token Authentication. Session Token Logout. Authentication Login Logout Update User Ping Send Hit Event Unique User Check. Introduction Get Resource Usage Update Resource Usage Get Browser Stats Get Country Stats Get Device Stats Get Language Stats Get OS Stats Get Page Stats Get Property Stats Get Referrer Stats Get Stat Summary Get Time Stats Get UTM Campaign Stats Get UTM Medium Stats Get UTM Source Stats Delete User Get Resource Usage Get User Info Update User Info Add Website Delete Website Get Website List Websites Update Website CLI Environment Variables Tracking Snippet Docker Fly.io Installation Railway Single Binary Automatic SSL Setup Click Events Overview Page Events Page Views Introduction Bounce Rate Location Metrics Overview Unique Visitors OpenAPI Specs openapi openapi-from-anchor-url-0 Optional Demo Discord GitHub ## What is Medama Analytics's llms.txt? Medama Analytics publishes an `/llms.txt` file that provides AI systems with a structured index of its documentation. It follows the [llms.txt specification](https://llmstxt.org), organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what Medama Analytics offers and where to find details. Pass Spec 3 Sections 58 Links 6.6 KB Size ~1.7k Tokens Sections: Docs · OpenAPI Specs · Optional ## Add Medama Analytics Docs to Your AI Assistant Select your tool to see how to add Medama Analytics's llms.txt as a documentation source. Cursor Windsurf Claude Code ChatGPT Zed Copilot 1. 1 Open any chat or composer panel 2. 2 Type @Docs and select "Add new doc" 3. 3 Paste the URL: https://oss.medama.io/llms.txt 4. 4 Wait for the green dot (indexing complete) 5. 5 Reference @Docs in chat when asking about Medama Analytics Cursor crawls the URL and indexes all subpages. Add a trailing slash to index child pages too. ## Spec Compliance 3 notes ## Frequently Asked Questions Where is Medama Analytics's llms.txt file? Medama Analytics publishes its llms.txt at https://oss.medama.io/llms.txt. This file provides a structured, markdown-formatted index of Medama Analytics's documentation that AI systems can consume to understand the project's APIs, guides, and references. How do I use Medama Analytics's llms.txt with AI coding assistants? Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of Medama Analytics's documentation so it can provide better code suggestions and answers about Medama Analytics. What does Medama Analytics's llms.txt contain? Medama Analytics's llms.txt contains 3 sections and 58 documentation links in 6.6 KB (~1.7k tokens). Key sections include Docs, OpenAPI Specs, Optional. How many tokens does Medama Analytics's llms.txt use? The concise llms.txt index is approximately 1.7k tokens (6.6 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline. Can I generate an llms.txt for my own project? Yes. Use the free llms.txt generator at mdream.dev/tools/llms-txt/generator to crawl your site and produce a spec-compliant llms.txt file. You can also validate existing files with the llms.txt validator. ## Browse More llms.txt Files [Libsodium documentation](https://mdream.dev/llms-txt/medama-analytics/llms-txt/libsodium-documentation) [iii iii (pronounced “three eye”) unifies your existing backend stack with a single engine and three primitives: Function, Trigger, and Worker.](https://mdream.dev/llms-txt/medama-analytics/llms-txt/iii) [nut.js Desktop automation library for Node.js. Control mouse, keyboard, and screen across Windows, macOS, and Linux.](https://mdream.dev/llms-txt/medama-analytics/llms-txt/nut-js) [Context7 MCP Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors](https://mdream.dev/llms-txt/medama-analytics/llms-txt/context7) [Laravel Herd](https://mdream.dev/llms-txt/medama-analytics/llms-txt/laravel-herd) [Vibe Kanban Get 10X more out of Claude Code, Codex or any coding agent](https://mdream.dev/llms-txt/medama-analytics/llms-txt/vibe-kanban) [每日一荐 LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)](https://mdream.dev/llms-txt/medama-analytics/llms-txt/leetcode) [https://qdrant.tech/ llms.txt Qdrant is a cutting-edge platform focused on delivering exceptional performance and efficiency in vector similarity search. As a robust vector database, it specializes in managing, searching, and retrieving high-dimensional vector data, essential for enhancing AI applications, machine learning, and modern search engines. With a suite of powerful features such as state-of-the-art hybrid search capabilities, retrieval-augmented generation (RAG) applications, and dense and sparse vector support, Qdrant stands out as an industry leader. Its offerings include managed cloud services, enabling users to harness the robust functionality of Qdrant without the burden of maintaining infrastructure. The platform supports advanced data security measures and seamless integrations with popular platforms and frameworks, catering to diverse data handling and analytic needs. Additionally, Qdrant offers comprehensive solutions for complex searching requirements through its innovative Query API and multivector representations, allowing for precise matching and enhanced retrieval quality. With its commitment to open-source principles and continuous innovation, Qdrant tailors solutions to meet both small-scale projects and enterprise-level demands efficiently, helping organizations unlock profound insights from their unstructured data and optimize their AI capabilities.](https://mdream.dev/llms-txt/medama-analytics/llms-txt/qdrant) [View all 99 projects ](https://mdream.dev/llms-txt/medama-analytics/llms-txt) ## Related Tools [

llms.txt Generator

Generate an llms.txt for your own project.](https://mdream.dev/llms-txt/medama-analytics/tools/llms-txt/generator) [

llms.txt Validator

Validate your llms.txt against the official spec.](https://mdream.dev/llms-txt/medama-analytics/tools/llms-txt/validator) © 2026 [Harlan Wilton](https://github.com/harlan-zw) · [MIT](https://github.com/harlan-zw/mdream/blob/main/license) [GitHub](https://github.com/harlan-zw/mdream) [Discord](https://discord.com/invite/275MBUBvgP)