markitai

io.github.YnewtimePublished by GitHub account Ynewtimev2.3.2Updated Oct 29, 2026

Convert documents, images and web pages to clean Markdown, for agents: single, URL and batch tools.

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Server details

Identifier: io.github.Ynewtime/markitai
Transport: STDIO
Runtime: Desktop only
Trust: Verified
Published: Sep 16, 2026

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Overview

AI-generated overview

Markitai converts documents, images and web pages into clean Markdown, giving an assistant single-file, URL and batch conversion tools.

What you can do: Convert a single document, image or web page into Markdown
Convert from a URL, which requires network access
Batch-convert a whole folder and produce a report
Run local OCR on scanned images, with optional model enhancement
When to use it: Useful when an assistant needs to read or reuse content locked in Office files, PDFs, scans or web pages as Markdown, including converting many files at once for later indexing or editing.
Requirements: Runs as a local stdio process, launched with uvx from the PyPI package markitai (Python 3.10+), or via the standalone CLI installers. Optional components: OCR models, Chrome/Chromium for JavaScript pages and LibreOffice for Office page images. URL inputs need network access. MARKITAI_HOME sets the config, cache and model directory; MODEL plus a matching provider API key enable LLM enhancement.

Before you install

Plain conversion needs no model connection, but LLM enhancement sends content to the configured provider using its credentials. URL inputs fetch remote pages, so content leaves the machine. Conversion writes output files to the chosen destination, and batch runs can overwrite existing results.

Installation

In SourceWeft

Open markitai in the dashboard and add it to a workspace.
Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Markitai

Markitai converts documents, web pages and images to Markdown. A single Rust core powers the markitai command (alias mkai), a local REST service with a browser workspace, an MCP server, and in-process Node.js, Python and Go bindings. The CLI executable needs no Python, Node.js or Go runtime; language bindings need their respective language runtime.

Markitai 2.0 is the Rust rewrite of Python markitai 1.2. See the changelog and compatibility contracts.

Install

macOS and Linux:

Windows (PowerShell):

The setup scripts download the release archive for your machine from GitHub Releases, check it against the release's SHA256SUMS, and install markitai, mkai and markitai-mcp for the current user, without administrator rights. Releases cover macOS 11+ (Apple silicon, Intel), Linux with glibc 2.28+ (x86-64, ARM64) and Windows (x64, ARM64). Python users can instead run pip install markitai or uv tool install markitai (Python 3.10+). PyPI has wheels for these six platforms only and no 1.x any more: elsewhere pip has nothing to install and leaves an installed 1.x as it is. Manual downloads, updates, uninstalling and going back to 1.x are in the installation steps.

The archives include license notices and selected Markdown guides for offline use. OCR models, Chromium and LibreOffice are optional separate components. See platform support for requirements, unsigned macOS builds for Gatekeeper, and bindings for language packages.

Quick start

markitai report.docx -o out/                  # writes out/report.docx.mdmarkitai ./documents -o out/                  # whole folder, with a reportmarkitai scan.png --ocr -o out/               # local OCR; models may need preparationmarkitai report.docx -o out/ --json           # structured result for automationmarkitai doctor                              # inspect optional componentsmarkitai --help                              # commands, options and examplesmarkitai serve                               # browser workspace on 127.0.0.1:3600

markitai report.docx -o out/                  # writes out/report.docx.mdmarkitai ./documents -o out/                  # whole folder, with a reportmarkitai scan.png --ocr -o out/               # local OCR; models may need preparationmarkitai report.docx -o out/ --json           # structured result for automationmarkitai doctor                              # inspect optional componentsmarkitai --help                              # commands, options and examplesmarkitai serve                               # browser workspace on 127.0.0.1:3600

For a separate trial state, set MARKITAI_HOME before using the CLI: export MARKITAI_HOME="$PWD/.local/try-home". Plain document conversion does not need a model connection. Existing configuration still applies; use --no-llm -b native for local document processing without model enhancement. URL inputs still need the network, even with --no-remote-fetch. Local OCR uses the portable Paddle engine on every platform (macOS Vision with MARKITAI_OCR_BACKEND=vision); doctor --fix can prepare missing Paddle models before offline use. JavaScript pages need Chrome/Chromium; Office page images need LibreOffice. Model enhancement (--llm) uses configured provider credentials or a subscription runtime.

Documentation

Quick start: installation and the first ten tasks.
CLI and MCP: command and Agent contracts.
Agent index and standalone Agent guide: plain Markdown entry points, also included in CLI archives.
Documentation index: the full source-checkout documentation. The offline archive contains selected guides; other topic links require this repository checkout.

License

MIT; see LICENSE and NOTICE.

Source: README.md at commit ef72fdc

Tools

SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

v2.3.2LatestOct 29, 2026
v2.3.0Oct 26, 2026
v2.2.0Oct 26, 2026
v2.1.0Oct 25, 2026
v2.0.0Oct 24, 2026
v1.2.0Sep 28, 2026
v1.1.0Sep 16, 2026

Score

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