Convert X (Twitter) posts into clean, LLM-ready Markdown with a simple URL swap.
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Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Simplifies X content ingestion for LLMs and AI agents
Biggest con
Credit-based system for advanced features like threads and metadata
TL;DR - tweet.md
- Converts X (Twitter) posts to clean Markdown for LLMs.
- Optimized for AI agents and research, saving tokens.
- Simple URL replacement for easy content transformation.
Pricing: Free plan available
Best for: Growing teams
What is tweet.md?
This tool transforms X (formerly Twitter) posts and threads into a clean Markdown format, optimized for use with Large Language Models (LLMs), AI agents, and research purposes. By simply replacing "x.com" with "tweet.md" in any X post URL, users can obtain a structured, token-efficient text output that eliminates the need for manual parsing of complex HTML, embeds, or JSON.
It is designed for anyone working with AI chatbots, agents, or performing research that requires ingesting X content. The service ensures that the full context of posts and threads, including author metadata, is preserved and presented in a format that LLMs can reliably process, preventing issues like missing content or broken links often encountered when feeding raw X URLs to AI. It offers integrations and guides for popular AI platforms like OpenAI's ChatGPT, Claude, and Gemini, and supports agent-based workflows with a dedicated skill.
Available on: Web
Pros & Cons
Pros
- Simplifies X content ingestion for LLMs and AI agents
- Saves tokens by providing clean, structured text
- Ensures full context and metadata are preserved
- Easy to use with a simple URL modification
- Compatible with a wide range of AI chat assistants and agents
Cons
- Credit-based system for advanced features like threads and metadata
- Free tier has limitations on conversions and features
- Relies on a session cookie or API key for paid features
Key Features
X.com to tweet.md URL replacement for conversionOutputs LLM-ready Markdown formatSupports full thread conversion (up to 100 posts)Includes author metadata in outputProvides an API key for agents and scriptsOffers an Obsidian-friendly output format with YAML frontmatterUtilizes official X API for data retrieval
Pricing
Freemium
tweet.md offers a generous free tier with optional paid upgrades for advanced features.
Reviews
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tweet.md FAQ
How does tweet.md help with AI research?
tweet.md transforms X posts and threads into a clean Markdown format, which is optimized for ingestion by Large Language Models (LLMs) and AI agents. This structured output ensures that the full context and metadata of X content are preserved for reliable processing in research.
What kind of user benefits most from tweet.md?
tweet.md is designed for anyone working with AI chatbots, agents, or performing research that requires ingesting X content. It is particularly useful for users who need to feed X posts and threads into LLMs without manual parsing or content loss.
How is tweet.md priced?
tweet.md offers a free tier for basic usage and features. For more extensive usage and advanced features like full thread conversion and metadata inclusion, paid plans are available, operating on a credit-based system.
What are the limitations of tweet.md?
Advanced features, such as converting full threads and including comprehensive metadata, operate on a credit-based system. The free tier also has limitations on the number of conversions and available features, requiring a session cookie or API key for paid functionalities.
Which AI platforms does tweet.md integrate with?
tweet.md offers integrations and guides for popular AI platforms, including OpenAI's ChatGPT, Claude, and Gemini. It also supports agent-based workflows with a dedicated skill, ensuring broad compatibility with various AI tools.
How does tweet.md simplify content ingestion for LLMs?
tweet.md simplifies content ingestion by converting X posts into a clean, token-efficient Markdown format, eliminating the need for manual parsing of complex HTML or JSON. This ensures LLMs receive structured text, preventing issues like missing content or broken links.
Source: tweet.md