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.
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tweet.md FAQ
What is the primary benefit of using tweet.md over directly feeding an X URL to an LLM?
Directly feeding an X URL to an LLM often results in unreliable context, missing content, or broken links due to the complex nature of web pages. tweet.md calls the official X API and normalizes the posts into clean, LLM-readable Markdown, which saves tokens and provides a structured text output that LLMs can reliably process without needing to parse HTML, embeds, or JSON.
How does tweet.md handle X threads, and what are the associated costs?
With credits, you can convert full X threads by omitting 'thread' or setting 'thread=full' in the URL. This will walk the reply chain up to 100 posts by default. You are charged 1 credit per post returned in the response. The free tier only supports single-post conversions.
Can I integrate tweet.md with my AI agent, and how would I do that?
Yes, you can integrate tweet.md with your AI agent. You can provide your agent with a specific skill (e.g., 'npx skills add tweet-md/skill') and your API key. The skill instructs your agent to replace any x.com URL with tweet.md, allowing it to read tweets in an optimized Markdown format.
What are the different output formats available besides the default Markdown?
In addition to the default Markdown format (which includes stats, media, quotes, and articles), tweet.md also offers an 'obsidian' format. This format adds YAML frontmatter and vault-friendly headings, making it suitable for direct import into Obsidian. You can specify the format by appending '?format=' to any tweet.md URL.
How are credits consumed when converting X posts, especially with author metadata?
Each post returned consumes 1 credit. If you include author metadata by setting 'userinfo=author' or 'userinfo=all', an additional 2 credits are charged per unique author found in the output. Credit packs do not expire, and you can top up as needed.
Source: tweet.md