Mdtero Mdtero

AI research pre-processing workflow

Turn one paper into a structured research package your next step can actually use

Mdtero turns one paper into a clean Markdown package your agent can keep using for translation, comparison, and review work.

Agent first for beta. Use the extension when you need local capture into a structured research package.

Connect Mdtero to the agent you already use

Install details live in Account. Beta onboarding starts there, then you paste the same setup into your agent.

OpenClaw

OpenClaw

Best for longer research runs with your own OpenClaw node.

Claude Code

Claude Code

Best when Mdtero should stay inside your editor loop.

Codex

Codex

Best for terminal-native Codex workflows.

Gemini CLI

Gemini CLI

Best for CLI-first Gemini workflows.

Open Account, generate the install message, then paste it into your agent.

01

Markdown Clean structure for reading and prompting

02

Figures Downloaded and linked for reuse

03

Translation Aligned with the same paper structure

04

Bundle Ready for your next agent step

Agent first. Extension second.

Start in Account when Mdtero should live inside your agent. Use the extension when you need local capture from a live paper page.

Agent

Agent Handoff

Create a key, copy one install message, and keep the whole workflow inside your agent.

Open Account
Extension

Browser Extension

Use this when you are already reading a supported page and want the fastest local capture path.

Open Edge listing

From discovery to literature work in four steps

1

Capture the paper you actually want

Start from a DOI, a supported paper page, arXiv, or a local retrieval helper and keep the acquisition path explicit.

2

Turn papers into a structured research package

Get Markdown, figures, downloadable artifacts, and machine-usable task results instead of a fragile one-off scrape.

3

Translate, organize, and preserve evidence

Use translation only when needed, while keeping the package auditable and ready for downstream review or synthesis.

4

Hand it off to your next agent step

Move straight into summarization, review drafting, weekly discovery loops, or your own research automation.

Three agent-ready research jobs

These examples map directly onto the current workflow: discovery, translation reading, and evidence-preserving review work.

Pair Semantic Scholar discovery with a reproducible capture loop

Use Semantic Scholar to surface new papers, then feed the shortlisted links into Mdtero so each candidate becomes a consistent package for screening and note taking.

Every Friday, collect this week's promising papers from Semantic Scholar, send the selected links through Mdtero, and return a shortlist with package links and one-line relevance notes.

Translate a paper without losing its research structure

Run Mdtero's built-in translation on top of the parsed package and get a cleaner target-language Markdown copy that keeps the same sections, figures, and references.

Parse this paper with Mdtero, run the built-in Chinese translation, and return the translated Markdown with the same section, figure, and reference anchors preserved.

Draft a literature review from evidence-preserving packages

Once a set of papers is normalized into the same package format, your agent can compare claims, extract methods, and draft a review without fighting format drift.

Compare these Mdtero packages, group them by method and evidence type, then draft a literature review outline with citations back to each paper package.

Simple pricing for research reading, translation, and review work

Free

Start with the core workflow.

  • 30 parses / mo
  • 3 translations / mo
  • Source file downloads

$3.9 / month

Default for most researchers who want the best value month to month.

  • 120 parses / mo
  • 30 translations / mo
  • Priority processing

$7.9 / month

More room for heavier review, comparison, and synthesis work.

  • 300 parses / mo
  • 100 translations / mo
  • Priority processing

$2 / pack

Add this when you only need more translations without changing plans.

  • 20 translations / pack
  • Translation only
  • Best for topping up after plan quota

API pay-as-you-go stays available for flexible product and automation use, but plans remain the default path for most researchers.

What researchers usually ask before they commit a workflow to it

What is supported right now?

Today Mdtero already supports supported paper-page capture, DOI-led parsing, arXiv-friendly flows, translation, and agent/API handoff on the same product surface.

Do I have to change my whole research workflow to use it?

No. Mdtero is designed as a preprocessing layer that fits into your current reading, note-taking, API, and agent workflows.

Is translation mandatory?

No. Translation is optional. The core product is the structured package that makes the next research step easier.

How does payment work at launch?

Plans cover routine usage first with included monthly quota. Translation add-ons top up extra translation volume, balance remains available for flexible use, and API pay-as-you-go is there for product or automation workflows.

I'm new here — what is an .md file?

An .md file is a Markdown file: plain text with lightweight formatting for headings, lists, tables, links, and images. Mdtero uses it because both humans and agents can read it cleanly. If you want the easiest viewer, open it in Typora; VS Code and many note apps also work well.

My OpenClaw runs on a server and cannot use a campus IP. What should I do?

Use a split workflow. Keep Elsevier or ScienceDirect acquisition on a machine that really has the right local network conditions — usually your own computer with the Mdtero local helper or browser extension. Then send the resulting Markdown or bundle to your server-hosted OpenClaw.