pullmd

Active·★ 480·AGPL-3.0·Updated 2026-09-03

★ Trending★ Hidden Gem

PullMD is a self-hosted service that converts various content types, including web pages, documents, images, audio, and YouTube videos, into clean, readable Markdown format. It supports integration with AI agents, offering a token-efficient output and multiple API endpoints.

pullmd is currently grouped under Data Processing, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Converts URLs, documents, images, audio, and YouTube videos to clean Markdown. and Providing clean, distilled content from web pages, documents, and media to AI agents for better context understanding and token efficiency.. The listed license is AGPL-3.0, which is useful when adoption constraints matter. It also shows measurable community traction with 480 GitHub stars.

#URL-to-Markdown#Self-hosted#AI Agent Tooling#Content Extraction#Document Conversion#Multimodal Processing#Web Scraping

Features

01Converts URLs, documents, images, audio, and YouTube videos to clean Markdown.

02Self-hosted with a PWA frontend, REST API, and MCP server for AI agent integration.

03Auto-detects and processes Reddit and Hacker News threads with full comment trees.

04Supports high-quality PDF OCR and media captioning/transcription via OpenAI-compatible models.

05Emits token-efficient Markdown body by default, with rich metadata in YAML frontmatter.

Why choose it

+Converts URLs, documents, images, audio, and YouTube videos to clean Markdown.

+Providing clean, distilled content from web pages, documents, and media to AI agents for better context understanding and token efficiency.

+Covers 5 supported environments or platforms, which is helpful for broader deployment needs.

+Ships with a public repository and a AGPL-3.0 license, which makes adoption and review easier.

Trade-offs

!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.

Compatibility

Docker

Deployment

Verified via docs

AI Agents

Integration

Verified via docs

Web Browsers

Frontend

Verified via docs

Python

Sidecars

Verified via docs

Node.js

Backend Runtime

Verified via docs

Quick start

$ mkdir pullmd

$ cd pullmd

$ curl -O https://raw.githubusercontent.com/AeternaLabsHQ/pullmd/main/docker-compose.yml

$ docker compose up -d

Use cases

↳Providing clean, distilled content from web pages, documents, and media to AI agents for better context understanding and token efficiency.

↳Creating dynamic content feeds (e.g., subreddit feeds) using stable share IDs that automatically refresh.

↳Building a personal or team-wide knowledge base by converting various online and local content into a unified Markdown format.

↳Integrating with large language models and chat agents (like Claude, ChatGPT) as a specialized tool for robust web and document fetching.

How it compares

≈pullmd sits in the Data Processing category, so it makes more sense to evaluate it alongside tools like mirascope instead of in isolation.

≈If your main need is closer to "Providing clean, distilled content from web pages, documents, and media to AI agents for better context understanding and token efficiency.", that use case is a better lens for comparison than broad feature checklists alone.

≈pullmd uses a AGPL-3.0 license, and community traction are both easier to judge in category context.

Features

Why choose it

Trade-offs

Compatibility

Quick start

Use cases

How it compares

Alternatives

Related searches

Comments

Features

Why choose it

Trade-offs

Compatibility

Quick start

Use cases

How it compares

Alternatives

Related searches

Comments