# MDflow

> A clean, no-noise markdown editor in the browser. Organize notes in separate workspaces and folders, edit in Monaco, and publish any document at an unguessable public URL or share it privately by email. MDflow exposes an HTTP API and a Model Context Protocol (MCP) server — hosted remote (Streamable HTTP) and local (stdio) — so AI agents can read, create, update, organize, and share markdown documents.

## MCP server (for AI agents)

- Remote endpoint: https://mdflow.cz/api/mcp (MCP Streamable HTTP transport, stateless, JSON responses)
- Auth: either an OAuth access token or a Personal Access Token. Claude and the ChatGPT app connect with no token — add https://mdflow.cz/api/mcp as a custom connector and sign in (OAuth, auto-discovered via https://mdflow.cz/.well-known/oauth-protected-resource, RFC 9728; beta). Clients that send their own header (Claude Code, Cursor, OpenAI Responses API) use a Personal Access Token: `Authorization: Bearer mdf_...` (created at https://mdflow.cz/settings, requires Pro).
- Tools: list/create/rename/delete workspaces and edit workspace descriptions, list/get/create/rename/move/delete folders (each with full path and compounded description), update folder descriptions, list/get/create/rename/update/move/delete markdown documents (each with full path and compounded description), topic-based context retrieval optionally scoped to one workspace (mdflow_get_context), public link sharing (mdflow_update_document_sharing), and private email sharing (mdflow_list_document_shares, mdflow_add_document_share, mdflow_revoke_document_share, mdflow_revoke_all_document_shares).
- Unauthenticated requests receive 401 with a WWW-Authenticate challenge (carrying `resource_metadata` for OAuth discovery) and setup instructions in the JSON body.

## Pricing

- MDflow Pro is €4.99/month with a 7-day free trial. The free plan allows 100 documents and 5 images.
- Agent control — the REST API, the MCP server, and Personal Access Tokens — requires Pro.
- Pricing page: https://mdflow.cz/pricing · machine-readable twin: https://mdflow.cz/pricing.md

## Raw markdown

- Every shared document has a raw markdown twin: append `.md` to its share URL, e.g. https://mdflow.cz/share/<slug>.md and https://mdflow.cz/share/c/<slug>/<documentId>.md. Served as text/markdown with YAML frontmatter (title, canonical_url, md_url, visibility) and open CORS for public documents.

## Docs

- [MCP server](https://mdflow.cz/docs/mcp): Connect to the hosted remote MCP server or install the local stdio server. Lets MCP-capable agents (Claude Code, Claude Desktop, Codex, Cursor, OpenAI Responses API) fetch markdown documents, use folder context, manage documents, and control sharing in MDflow.
- [Public API](https://mdflow.cz/docs/api): HTTP API for folders, markdown documents, public sharing, and private email sharing, authenticated with a Personal Access Token. Human-readable reference for all endpoints.
- [Connect Claude](https://mdflow.cz/docs/claude): Step-by-step guide to connect Claude (claude.ai custom connector, Claude Code, Claude Desktop) to MDflow over MCP — OAuth sign-in with no token, or a Personal Access Token — with a troubleshooting table.
- [Connect ChatGPT](https://mdflow.cz/docs/chatgpt): Step-by-step guide to connect ChatGPT (app connector, Codex, the OpenAI Responses API, and custom GPT Actions) to MDflow over MCP — OAuth sign-in or a Personal Access Token — with a troubleshooting table.
- [OpenAPI specification](https://mdflow.cz/openapi.json): Machine-readable OpenAPI 3.1 description of the public API.
- [Agent control guide](https://mdflow.cz/docs.md): One self-contained markdown page describing how an AI agent controls MDflow — auth, all MCP tools, REST endpoints, and client connect configs.
- [Agent card](https://mdflow.cz/.well-known/agent-card.json): Machine-readable discovery card (skills, interfaces, auth) at the standard well-known location.
- [FAQ](https://mdflow.cz/faq): Frequently asked questions — what MDflow is, how to share markdown files and links, how to connect AI agents (Claude, ChatGPT) via MCP and the API, pricing, privacy, and how it compares to Notion, Google Docs, and Obsidian. Plain-markdown twin: https://mdflow.cz/faq.md

## Features

- [Markdown Tasks](https://mdflow.cz/markdown-tasks): MDflow's Tasks view (/tasks) aggregates every markdown checkbox (`- [ ]` / `- [x]`) across all documents in the active workspace into one filterable, editable list — by status (all/outstanding/completed), due date (due/overdue, today, this week, next week), and owner. Tasks stay as plain markdown lines in your documents (no separate task database), so they remain portable; an optional `(YYYYMMDD)` due date and `(email)` owner can follow the checkbox. Encrypted documents are skipped (parsed in the browser only), and because a task is just a document line, scripts and AI agents writing document bodies over the API or MCP can create tasks too. Available on every plan.
- [GitHub integration](https://mdflow.cz/docs/github): Connect a GitHub account to a workspace and edit the markdown in your repositories in place — browse repos, branches, and folders, then create, edit, rename, delete, and commit markdown files (commit-on-save, attributed to your account; files are read and written live, never copied into MDflow). A human, cookie-authenticated feature, not exposed to the API/MCP agent surface. Available on every plan.
- [Google Drive integration](https://mdflow.cz/docs/gdrive): Connect a Google Drive account to a workspace and edit the markdown files you pick from Drive — pick folders and .md files via Google's file picker, then open, edit, create, rename, and delete them (saves write back to the Drive file in place; deletes go to Drive trash; files are read and written live, never copied into MDflow). Uses Google's narrow drive.file per-file scope, so MDflow only sees files you pick or create, not your whole Drive. Experimental; a human, cookie-authenticated feature, not exposed to the API/MCP agent surface. Available on every plan.
- [VS Code extension](https://mdflow.cz/docs/vscode): Install the MDflow Workspace extension for VS Code to browse and edit your MDflow workspaces, folders, and markdown documents from the editor — a tree in the Explorer, documents open as native markdown tabs, Ctrl/Cmd+S saves back, full CRUD on workspaces/folders/documents, and per-file client-side encryption (byte-compatible with the web app and the mdflow-crypt CLI). Sign in with OAuth or a Personal Access Token, stored in the editor's encrypted Secret Storage. A human editor client of the HTTP API — requires Pro — not an agent surface. Install: https://marketplace.visualstudio.com/items?itemName=DataOps.mdflow-vscode
- [Cursor extension](https://mdflow.cz/docs/cursor): The same MDflow Workspace extension for Cursor, Windsurf, VSCodium, and other Open VSX editors — edit in the sidebar the same markdown your AI agent reads and writes over MCP, the human editor for your agent's memory. A human editor client of the HTTP API (requires Pro), installed from Open VSX; the agent side connects separately via the MCP server. Install: https://open-vsx.org/extension/DataOps/mdflow-vscode

## Tools

- [mdflow-crypt](https://mdflow.cz/mdflow-crypt): A standalone, zero-dependency npm CLI (`npx mdflow-crypt encrypt|decrypt <file>`) that encrypts and decrypts MDflow documents (mdflow-enc:v1) locally, using the same AES-256-GCM + PBKDF2 (600k iterations) crypto as MDflow's in-browser encryption. A human tool run on your own machine — plaintext and password never reach a server or an AI model, so agents must not run it. Plain-markdown twin: https://mdflow.cz/mdflow-crypt.md

## Comparisons

- [MDflow alternatives & comparisons](https://mdflow.cz/compare-note-taking): Honest, side-by-side comparisons of MDflow with the note apps people switch from.
- [The OneNote alternative](https://mdflow.cz/compare-note-taking/onenote-alternative): MDflow vs OneNote — real Markdown rendering, plain .md files you own, reliable search, sharing with comments, and API + MCP for AI agents.
- [The Evernote alternative](https://mdflow.cz/compare-note-taking/evernote-alternative): MDflow vs Evernote — open .md files, no artificial note limits, free offline editing, and API + MCP, from €4.99/month.
- [The Obsidian alternative](https://mdflow.cz/compare-note-taking/obsidian-alternative): MDflow vs Obsidian — markdown with zero setup, free cloud sync, clean reader sharing with comments, and a built-in MCP server (no plugin tax).

## Blog

- [MDflow blog](https://mdflow.cz/blog): Commentary and guides on markdown, AI agents, MCP, and standards like Google's Open Knowledge Format (OKF). Plain-markdown index: https://mdflow.cz/blog.md
- [Spec-Driven Development: Where Your Markdown Specs Should Live (2026)](https://mdflow.cz/blog/spec-driven-development-markdown-specs): A workflow guide to spec-driven development (SDD) — the 2026-standard practice of writing a markdown specification first and treating it as the source of truth your AI coding agent plans, generates, tests, and validates against, instead of one-off prompts that scroll away. Explains what SDD is and the phased shape all the leading tools share (spec → plan → tasks → implement, each phase a reviewable .md file), with the concrete file conventions: GitHub Spec Kit (120k+ stars, 30+ agents) writes spec.md/plan.md/tasks.md into specs/<feature>/ plus a constitution.md under .specify/memory/ via /speckit.specify, /speckit.plan, /speckit.tasks, /speckit.implement; AWS Kiro writes requirements.md (EARS "WHEN… THE SYSTEM SHALL…" notation)/design.md/tasks.md under .kiro/specs/; and agents also read AGENTS.md, CLAUDE.md, and llms.txt. Covers why SDD helps developers (front-loads the expensive decisions into reviewable intent — AWS reported ~40-hour features shipping in under 8 when authored spec-first — plus repeatability, an audit trail, and less prompt fatigue) and AI agents (a spec is structured context with acceptance criteria to test against and a task list to work through, and one source of truth multiple agents share without drift). The core argument answers the question most guides skip — where specs should live — by splitting them on lifespan and reach: feature specs and agent-instruction files (AGENTS.md/CLAUDE.md/llms.txt) belong in the repo beside the code, but durable cross-cutting specs (PRDs, architecture decision records, API contracts, coding standards, glossaries) are read by many repos and agents and outlive any branch, so they need a shared, versioned, agent-readable home. Shows how MDflow fits as that home: markdown-native storage agents already speak, folder descriptions as retrieval context ranked first by mdflow_get_context, read-AND-write access over the remote MCP server (Claude/ChatGPT via OAuth, Cursor/Codex/Claude Code via Personal Access Token) so agents pull the spec and write proposed updates back, automatic version history on every change for the audit trail, sharing for review, and raw .md twins with YAML frontmatter over open CORS so any tool/CI/agent can fetch the canonical spec by URL — plus a roadmap toward serving a whole collection of related specs as one cross-linked bundle. Plain-markdown twin: https://mdflow.cz/blog/spec-driven-development-markdown-specs.md
- [Web Clipper to Clean Markdown: Save Any Article Your AI Can Read (2026)](https://mdflow.cz/blog/web-clipper-markdown): What a web clipper is and why saving pages as clean markdown beats a bookmark (a pointer that rots) or a screenshot (an image you can't search) — a clipper is a browser extension that captures a page, runs a readability pass (the Mozilla Readability engine behind Reader View) to strip navigation, ads, and pop-ups, and converts the surviving article to clean markdown you own (greppable, portable, editable, version-controllable, and natively parseable by every LLM). Makes the 2026 case that the deciding factor is where clips land: a markdown clip is only useful to your AI if it lives somewhere agent-readable, which is where local-vault clippers fall short. Covers why clippers help you (read-it-later minus the rot, a cited research library with auto frontmatter, highlight-first reading, full-text search) and your AI (clips are the fresh, specific context a model's training cutoff lacks — ask Claude to summarize the three articles you saved and it reads the real clips), which use cases benefit most, and how MDflow's Web Clipper lines up today: clip any http/https page to clean markdown from a toolbar popup/side panel/embedded overlay/right-click/keyboard shortcut across Chrome and Chromium (Brave, Arc, Edge), Firefox desktop and mobile, and Safari on macOS/iOS/iPadOS; clip the full article, a text selection, or saved highlights; a web highlighter whose highlights persist across visits; templates auto-selected by URL pattern or schema.org data controlling name/folder/content/properties; typed frontmatter properties (author, source URL, date, tags); an Interpreter running natural-language prompts with your own provider key (Claude, OpenAI, Gemini, DeepSeek, Ollama, and more) that MDflow never sees or stores; and — the wedge vs the Obsidian Web Clipper's local vault — every clip saves into a hosted workspace reachable by mdflow_get_context (folder descriptions ranked first), the remote MCP server, the HTTP API, and raw .md twins with frontmatter over open CORS, so ChatGPT, Claude, Cursor, and Codex read your clips back as context. Free to install (clipboard/local .md with no account); saving into MDflow uses a Personal Access Token (Pro). Plain-markdown twin: https://mdflow.cz/blog/web-clipper-markdown.md
- [Encrypted Notes App: How to Keep Cloud Markdown Truly Private (2026)](https://mdflow.cz/blog/encrypted-notes-app): A decision-stage buyer's guide plus hands-on how-to for choosing an encrypted notes app that keeps cloud markdown truly private (companion to the deeper client-side-encryption explainer). Defines the bar for "truly private" — encryption at rest (provider holds the keys) vs client-side/end-to-end encryption (device encrypts before upload) vs zero-knowledge (the provider has zero knowledge of keys or plaintext), with the honest web-app ceiling that browser crypto defends against breach-at-rest, not a fully malicious provider. Gives a six-point checklist (client-side/zero-knowledge not just at-rest, a named modern cipher like AES-256-GCM or XChaCha20-Poly1305 plus a slow KDF, open/portable format, no-recovery honesty, cross-device access, a clear per-note AI stance) and an honest five-app comparison table — Standard Notes (E2EE-by-default XChaCha20-Poly1305, markdown paid-only, encrypts everything), Notesnook (open-source zero-knowledge, markdown), Joplin (markdown-native, optional bring-your-own-sync E2EE), Obsidian (local-first vault, paid E2EE Sync), and MDflow — highlighting that every strong app encrypts all-or-nothing, which locks AI agents out entirely. Argues the real unit of decision is the individual document (encrypt secrets like API keys/health/legal/journals; leave project notes/research/meeting docs agent-readable) and shows MDflow's wedge: per-document AES-256-GCM encryption in the browser with a PBKDF2-HMAC-SHA-256 600k-iteration key, server stores only opaque mdflow-enc:v1 ciphertext (title/folder names stay readable, body only), encrypted docs excluded from search and returned as ciphertext over the HTTP API and MCP while unencrypted docs stay retrievable via folder descriptions and mdflow_get_context, free on every plan, and no lock-in via the open-source zero-dependency mdflow-crypt CLI (npx mdflow-crypt encrypt/decrypt) that runs the identical scheme locally so plaintext never reaches a server or model. Plain-markdown twin: https://mdflow.cz/blog/encrypted-notes-app.md
- [Markdown Task Management: One List From Every Checkbox (2026)](https://mdflow.cz/blog/markdown-task-management): A use-case walkthrough of markdown task management — tracking to-dos as ordinary GitHub Flavored Markdown checkboxes (- [ ] open, - [x] done) inside your notes, and solving the scatter problem where those checkboxes end up spread across dozens of files with no single overview. Explains what markdown task management is and why the missing half is aggregation, why it helps developers/GTD practitioners (capture speed of plain text plus the overview of a real task manager, tasks born inside documents next to their context) and AI agents (a task is just text, so an agent writes a line and a task exists — a shared human/agent surface), which applications benefit most (project/sprint notes, client work, personal GTD/PKM, spec-driven and agentic development, meeting/research notes), and how MDflow's Tasks view lines up today: a dedicated /tasks view aggregates every checkbox across the active workspace into one Asana-style list grouped by folder and document with nested subtasks; no separate database because the checkbox line in the document body is the single source of truth (editing a task rewrites the source line and saves the document); optional due date (YYYYMMDD) and owner (email) as two parenthetical groups right after the checkbox; filter by status/due date/owner with live counts plus text search; inline edit with overdue red and today amber; capture inline, via a top-level quick-add to a Tasks document, or by any script or AI agent that writes a document body over the HTTP API or MCP; client-side-encrypted documents counted and skipped, all parsing in the browser. Honest scope: scoped to the active workspace, aggregates checkboxes rather than being a full project manager, available on every plan (not Pro-gated). Plain-markdown twin: https://mdflow.cz/blog/markdown-task-management.md
- [Markdown to PDF, Word, HTML: The Conversion Playbook (2026)](https://mdflow.cz/blog/convert-markdown-to-pdf-word-html): The complete multi-format playbook for converting Markdown to the three formats people actually ask for — PDF, Word (.docx), and HTML — with the reliable method per target and copy-paste commands. The organizing idea: every converter parses Markdown into a structured document and then renders it, so Pandoc (which parses once into an abstract syntax tree and renders to 40+ formats) is the single tool that does all three well — pandoc doc.md -o doc.pdf (add --pdf-engine=xelatex for system fonts), pandoc doc.md -o doc.docx (a genuine editable .docx with real Word heading styles, and --reference-doc=house-style.docx to apply a corporate template's styles/margins/fonts/headers — the only reliable path to Word, since copy-paste and browser-engine tools produce fakes), and pandoc doc.md -s -o doc.html (standalone page; add --embed-resources -c style.css to inline CSS and images into one portable file, vs a bare HTML fragment from any Markdown library like markdown-it/marked/remark/Python-Markdown). Covers fast no-install options (editor export, print-to-PDF), what survives conversion (standard formatting maps to native constructs; raw HTML embeds mostly don't reach Word; footnotes/math need flags), which applications benefit (docs teams, reports, academic writing, static sites, AI pipelines), and how MDflow lines up today: one-click print-ready PDF export in the editor and shared-document reader, download the original .md any time, raw .md twins over the HTTP API, MCP access, and whole-workspace .md archive export — then run Pandoc on that portable .md for Word and HTML. Links to the dedicated five-ways Markdown-to-PDF deep dive. Plain-markdown twin: https://mdflow.cz/blog/convert-markdown-to-pdf-word-html.md
- [The Best Second Brain App When Your AI Reads It Too (2026)](https://mdflow.cz/blog/best-second-brain-app): A personal-knowledge-management (PKM) shortlist reframed for the AI era — a second brain app is a tool for capturing and retrieving notes (from Tiago Forte's Building a Second Brain and its CODE method: Capture, Organize, Distill, Express, plus the PARA structure), but the 2026 deciding factor is whether your AI can read it too. Judges the classic second brain apps on one new axis — can ChatGPT or Claude actually read and write it: Notion (best all-in-one but a proprietary block database reached only through Notion's own API), Obsidian and Logseq (local-first plain-Markdown vaults you own, but AI access is self-assembled local plugins/servers the web ChatGPT app and phones can't reach), Evernote/Bear (capture-first, local or proprietary, no remote agent surface — Bear is Apple-only), AI-native notebooks like Mem and Reflect (AI baked in, but the vendor's AI wired to their storage), and MDflow (the agent-ready pick: hosted Markdown with a first-party remote MCP server at https://mdflow.cz/api/mcp and a full HTTP API so ChatGPT over OAuth, Claude, Cursor, and Codex read AND write the same notes from any device). Explains why MCP reframes PKM, what an agent actually needs from a second brain (always-on HTTPS endpoint, plain-Markdown parsing, curated retrieval not a raw dump, safe write-back with version history), a five-group which-app-for-whom guide, and how MDflow lines up today (raw .md twins with YAML frontmatter over open CORS, folder descriptions ranked by mdflow_get_context, automatic version history on every write path, Web Clipper capture, sharing/comments, AES-256 encryption, llms.txt/agent card/OpenAPI discovery) plus a roadmap. Plain-markdown twin: https://mdflow.cz/blog/best-second-brain-app.md
- [Basic Memory vs Hjarni vs MDflow (2026)](https://mdflow.cz/blog/basic-memory-vs-hjarni-vs-mdflow): A focused three-way head-to-head of the markdown-native MCP knowledge bases — Basic Memory, Hjarni, and MDflow — for people who have already decided they want plain Markdown (the wider survey that also covers mem0 and Obsidian is the separate best-mcp-knowledge-base roundup). Establishes the shared core all three have (plain .md files you own, a built-in MCP server, read AND write, folders with human-written instructions) and then frames the choice as three axes rather than a single winner: (1) self-hosted or hosted — Basic Memory is local-first, open source (AGPL-3.0), free on your own disk, with a paid ~$15/mo Cloud tier for hosted DB/sync/mobile; Hjarni and MDflow are hosted-only with nothing to install and any-device (phone) reach by default; (2) AI memory or a real workspace — Hjarni is a clean memory-first app (free up to 25 notes, Pro $10/mo unlimited + attachments + public folder links, Teams $13/seat, custom AI instructions per folder/team/account, ZIP export) while MDflow is a document workspace with a real editor (split preview, folder tree, workspaces, search) that the MCP layer wraps; (3) how much governance — MDflow adds automatic version history on every write path (editor, API, agent) with line diffs and one-click restore, sharing, collections, anchored comments, and client-side AES-256 encryption, where Basic Memory leans on files + Git or Cloud audit logs and Hjarni is memory-first without full per-document history. Includes a nine-row comparison table, a which-application-benefits list, MDflow's current-features section (hosted remote MCP at https://mdflow.cz/api/mcp, mdflow_get_context ranking folder descriptions, write-back, raw .md twins with frontmatter over open CORS, llms.txt/agent card/OpenAPI discovery), and a roadmap. Plain-markdown twin: https://mdflow.cz/blog/basic-memory-vs-hjarni-vs-mdflow.md
- [Best Notion Alternatives for Markdown People (2026)](https://mdflow.cz/blog/best-notion-alternatives-for-markdown): An honest roundup of the best Notion alternatives for people who live in markdown — why Notion's proprietary block model makes its markdown a lossy export (databases become CSV, callouts become HTML, filenames carry UUIDs) and what markdown-as-source-of-truth means instead, then seven picks compared with a features table: Obsidian (the default local-first vault, biggest plugin ecosystem, free personal + paid Sync), Logseq (open-source outliner for daily notes and backlinks, migrating toward a database version), Joplin (open source with real end-to-end encryption and self-hostable sync), Bear (Apple-only, beautiful, stores a DB with markdown export rather than plain .md on disk), Anytype (local-first and E2E encrypted but object-based, markdown only via export), Zettlr (free open-source markdown editor for academic long-form with Pandoc/Zotero), and MDflow (the agent-ready pick). The 2026 differentiator the roundup argues most miss: every local-first alternative is unreachable by an AI agent over the network, whereas MDflow is hosted AND markdown-native — the same plain .md that is the source of truth is reachable at a raw .md URL with open CORS, a hosted MCP server, and a read/write HTTP API with Personal Access Tokens, so ChatGPT, Claude, Cursor, and Codex read and write it without a local sync folder. Honest caveat throughout: none of them replace Notion's relational databases; run both. Plain-markdown twin: https://mdflow.cz/blog/best-notion-alternatives-for-markdown.md
- [MDflow Mobile: A Markdown App for iPhone and iPad (2026)](https://mdflow.cz/blog/mdflow-mobile-app): A walkthrough of MDflow's free native iOS companion app (App Store: MDflow Mobile Markdown, id6785617933) — built in SwiftUI with iOS 26 Liquid Glass, universal for iPhone and iPad, no tracking. It signs into the same MDflow account as the web via Sign in with Apple, Google, GitHub, or Microsoft (same Supabase backend), then lets you switch workspaces, walk an arbitrarily deep folder tree with a Favorites section and pull-to-refresh, search the whole workspace by title and body, read GitHub-Flavored Markdown (headings, lists, task lists, tables, code blocks, blockquotes, images) via swift-markdown-ui/cmark-gfm with an Edit/Preview toggle and persistent text zoom, and edit with debounced autosave showing a Saving/Saved/Not saved indicator. You can create (auto .md titles), rename, move, delete, and favorite documents and create nested folders. Two mobile-first pillars: (1) on-device document encryption — AES-256-GCM with PBKDF2-HMAC-SHA256 at 600,000 iterations in the same mdflow-enc:v1 format as the web app, so a note encrypted in the browser opens on the phone, with Face ID / Touch ID unlock after the first password entry and an explicit no-recovery warning; and (2) Share to MDflow, a system share-sheet extension that captures text or files from any app (queued offline via an App Group and imported into an "iOS" folder on next launch). Honest scope: it is a companion to the web workspace — no offline editing (autosave needs a connection), and image upload, in-app sharing/collections/comments, version history, the aggregated Tasks view, and the split editor stay on the web; no macOS app. Fits alongside the web editor, the HTTP API, and the remote MCP server that AI agents use. Plain-markdown twin: https://mdflow.cz/blog/mdflow-mobile-app.md
- [MDflow vs Obsidian for the AI Era (2026)](https://mdflow.cz/blog/mdflow-vs-obsidian-ai-era): An honest MDflow vs Obsidian comparison reframed for the AI era — both store plain Markdown you own, but the split is local-first vault versus hosted workspace, and self-assembled AI versus built-in agent access. Covers where Obsidian wins (fully offline editing, a huge community plugin ecosystem, files that never leave your disk) and where MDflow wins (cloud sync included instead of paid Obsidian Sync, sharing with comments, and a first-party remote MCP server at https://mdflow.cz/api/mcp plus a full HTTP API so ChatGPT over OAuth, Claude, Cursor, VS Code, and Codex read and write the same notes from any device — versus Obsidian's local-only community MCP plugins that the web ChatGPT app and phones cannot reach), why MCP reframes the comparison, a six-category "which tool for whom" guide, and how MDflow already lines up (raw .md twins with YAML frontmatter over open CORS, folder descriptions ranked by mdflow_get_context, automatic version history on every write path, sharing/collections/encryption, llms.txt + agent card + OpenAPI discovery) with a roadmap toward team-governed shared workspaces. Plain-markdown twin: https://mdflow.cz/blog/mdflow-vs-obsidian-ai-era.md
- [How to Adopt Google's Open Knowledge Format (OKF) in 2026](https://mdflow.cz/blog/open-knowledge-format-adoption-guide): A hands-on adoption guide for Google's Open Knowledge Format — what firmed up since the June 12, 2026 v0.1 launch (a precise SPEC.md vocabulary: Knowledge Bundle as the unit of distribution, a Concept as one markdown file, a Concept ID as the file path without .md, the new reserved log.md for change history, okf_version in the root index.md, absolute bundle-relative vs relative cross-links, and liberal conformance where only a non-empty `type` is required and consumers must tolerate unknown fields and broken links), a six-step tutorial to build a conformant bundle by hand (pick a concept, write a frontmatter+markdown concept file, add index.md for progressive disclosure, cross-link with /-rooted Concept IDs, keep a log.md, distribute as a git repo) with a conformance checklist, why it helps developers and AI agents, which applications benefit most, and how MDflow already lines up (markdown-native storage, cascading folder descriptions ≈ index.md, automatic version history ≈ log.md, raw .md with YAML frontmatter over open CORS, and producer/consumer access over MCP and the HTTP API) plus a roadmap toward native type/tags and OKF import/export. Plain-markdown twin: https://mdflow.cz/blog/open-knowledge-format-adoption-guide.md
- [Turn ChatGPT Chats into a Searchable Markdown Knowledge Base](https://mdflow.cz/blog/export-chatgpt-to-markdown): A step-by-step how-to for turning ephemeral ChatGPT conversations into a searchable markdown knowledge base you own — why a chat log is not a knowledge base (weak search, no structure, one-app lock-in, memory ≠ archive), how to get conversations out of ChatGPT (Share → Create Link for a public chatgpt.com/share page, or Settings → Data Controls → Export data for a whole-account conversations.json + chat.html zip that is JSON/HTML, not markdown, and expires in 24h), how to convert a shared conversation to clean markdown with the MDflow Web Clipper (auto-extract, choose folder, URL-pattern templates, frontmatter properties, and an Interpreter that summarizes with your own LLM key), how to make the archive searchable (workspace full-text search over titles and bodies with snippets, folders whose descriptions add cascading context, editable docs with version history), and how to let your AI read it back over MCP and the HTTP API via mdflow_get_context so ChatGPT, Claude, Cursor, and Codex reuse your past conversations as context. Plain-markdown twin: https://mdflow.cz/blog/export-chatgpt-to-markdown.md
- [Build a Portable AI Memory You Own (ChatGPT + Claude)](https://mdflow.cz/blog/portable-ai-memory): Why ChatGPT's and Claude's built-in memory isn't enough — each is a per-vendor silo that works only inside its own app (ChatGPT's saved memories plus year-long chat-history reference; Claude's daily-synthesized, per-Project memory) and that you don't own as a portable file, so switching tools means re-explaining yourself again. What a "portable AI memory you own" is (curated plain markdown you control, read and written by every assistant over the open Model Context Protocol or an HTTP API), who needs one most (multi-tool users, developers across editors, founders and consultants), and a four-step build walkthrough with MDflow: a described folder as the retrieval signal, context authored once, Claude and the ChatGPT app connected over OAuth (no token to paste, beta, Pro) or header clients with a Personal Access Token, and agent write-back with automatic version history — plus a raw .md twin behind every document and one endpoint every client shares. Contrasts with local-first Basic Memory. Plain-markdown twin: https://mdflow.cz/blog/portable-ai-memory.md
- [AI Agent Memory vs RAG vs a Plain Markdown File (2026)](https://mdflow.cz/blog/ai-agent-memory-vs-rag-vs-markdown): An honest three-way comparison of the ways to give an AI agent persistent context — dedicated memory systems (mem0, Zep, Letta), retrieval-augmented generation (RAG), and a curated plain-markdown knowledge base — with the benchmarks that matter (Chroma's "context rot" study, the "lost in the middle" finding, the contested mem0/Zep/Letta scores), why a bigger context window is not the answer, which application fits which approach, and how MDflow is the middle path: hosted markdown you own with a keyword-ranked folder-description retrieval layer instead of a vector database, agent write-back over MCP and the API, raw .md twins, and automatic version history. Plain-markdown twin: https://mdflow.cz/blog/ai-agent-memory-vs-rag-vs-markdown.md
- [Let AI Agents Write to Your Knowledge Base, Not Just Read It](https://mdflow.cz/blog/ai-agents-write-to-knowledge-base): Why most agent-memory setups are read-only, what write-back means (create, update, move, delete vs search-only), why letting an agent do the bookkeeping keeps a knowledge base current instead of stale, which workflows benefit most (agentic coding, self-maintaining wikis, meeting notes, living docs, task automation), and how to let Claude, ChatGPT, Cursor, and Codex write to MDflow with a revocable Personal Access Token over the MCP server or HTTP API — with automatic version history behind every agent edit so write-back is safe and reversible. Plain-markdown twin: https://mdflow.cz/blog/ai-agents-write-to-knowledge-base.md
- [The Best MCP Knowledge Base for ChatGPT & Claude (Honest 2026 Comparison)](https://mdflow.cz/blog/best-mcp-knowledge-base): An honest, vendor-written comparison of the best MCP knowledge base options for ChatGPT and Claude — MDflow, Hjarni, Basic Memory, mem0, and Obsidian — across built-in MCP server, read+write, plain-markdown ownership, multi-client support, hosted vs self-hosted, and governance, with a best-for verdict for each and a decision guide for choosing. Plain-markdown twin: https://mdflow.cz/blog/best-mcp-knowledge-base.md
- [Folder Descriptions as Agent Context: Retrieval Without a Vector Database](https://mdflow.cz/blog/folder-descriptions-agent-context): How human-written folder descriptions become a curated retrieval signal an AI agent can rank with plain keyword scoring — no embeddings, no vector database, no reindexing — how that differs from RAG and when each fits, and how MDflow's mdflow_get_context weights folder descriptions highest (then folder names and document titles) over live markdown, with a compounded workspace→folder context cascade and agent write-back to keep the signal current. Plain-markdown twin: https://mdflow.cz/blog/folder-descriptions-agent-context.md
- [llms.txt Explained: The robots.txt for AI and How to Ship a Good One](https://mdflow.cz/blog/llms-txt-explained): What llms.txt is, what a good one looks like (using MDflow's own as the worked example), the common mistakes, how it differs from robots.txt, sitemap.xml, and AGENTS.md, and whether it is worth shipping. Plain-markdown twin: https://mdflow.cz/blog/llms-txt-explained.md
- [How to Give ChatGPT and Claude Access to Your Notes (Remote MCP)](https://mdflow.cz/blog/connect-chatgpt-claude-to-your-notes): What a remote MCP server is (an MCP server you reach over HTTPS instead of running locally), why it removes setup for people and grounds AI agents in real markdown, which clients can connect to an authenticated remote server with a Personal Access Token today (Claude Code, Cursor, VS Code, the OpenAI Responses API, and Claude Desktop via the mcp-remote bridge) and where the ChatGPT app and Claude.ai now connect over OAuth (a custom-connector sign-in, no token to paste, in beta), and how MDflow's hosted server at https://mdflow.cz/api/mcp, mdflow_get_context retrieval, write-back tools, and raw .md twins fit. Plain-markdown twin: https://mdflow.cz/blog/connect-chatgpt-claude-to-your-notes.md
- [The Best Notion Alternative for Markdown People](https://mdflow.cz/blog/notion-alternative-for-markdown): An honest MDflow vs Notion comparison for people who live in markdown — why Notion's proprietary block model makes its markdown export lossy (databases become CSV, callouts become HTML), how markdown-as-source-of-truth differs from markdown-as-export, where Notion still wins (databases, real-time collaboration, non-technical teams), and how MDflow serves raw .md with frontmatter plus a first-party MCP server and full API for AI agents. Plain-markdown twin: https://mdflow.cz/blog/notion-alternative-for-markdown.md
- [Context Engineering for AI Agents: Curation Beats a Bigger Prompt](https://mdflow.cz/blog/context-engineering-for-ai-agents): Why the 2025 shift from prompt engineering to context engineering matters, why a bigger context window makes agents worse (the "context rot" effect), and how MDflow's folder descriptions and mdflow_get_context make curated, just-in-time retrieval a first-class primitive. Plain-markdown twin: https://mdflow.cz/blog/context-engineering-for-ai-agents.md
- [Markdown to PDF: The 5 Reliable Ways (and When to Use Each)](https://mdflow.cz/blog/markdown-to-pdf): The five reliable ways to convert markdown to PDF — editor/browser export, Pandoc, command-line tools, print-to-PDF, and conversion APIs — with honest pros and cons for page breaks, fonts, and YAML frontmatter, plus how MDflow's built-in print-ready PDF export fits. Plain-markdown twin: https://mdflow.cz/blog/markdown-to-pdf.md
- [MCP and A2A: The Protocols Powering Agentic Interfaces](https://mdflow.cz/blog/mcp-and-a2a-agentic-interfaces): What the Model Context Protocol (MCP) and Agent2Agent (A2A) protocols are, how they differ (MCP connects agents to tools, A2A connects agents to each other), why they matter for developers and AI agents, and how MDflow ships an MCP server plus an A2A agent card today. Plain-markdown twin: https://mdflow.cz/blog/mcp-and-a2a-agentic-interfaces.md
- [Google's Open Knowledge Format (OKF): What It Means for Developers and AI Agents](https://mdflow.cz/blog/google-open-knowledge-format-okf): What OKF is, why it matters for developers and AI agents, which applications benefit most, and how MDflow's markdown-native, agent-ready model aligns with it. Plain-markdown twin: https://mdflow.cz/blog/google-open-knowledge-format-okf.md
- [Client-Side Encryption for Notes You Store Online](https://mdflow.cz/blog/client-side-encryption-for-online-notes): What client-side encryption is (encrypt in the browser, server stores only ciphertext), how it differs from zero-knowledge and end-to-end encryption, the cloud-vs-self-hosted convenience/security tradeoff, which documents need it most, and how MDflow encrypts document bodies with AES-256-GCM and PBKDF2 (600k iterations) entirely in your browser — plus the deliberate tradeoff that encrypted docs are excluded from search and opaque to AI agents. Plain-markdown twin: https://mdflow.cz/blog/client-side-encryption-for-online-notes.md
- [Version Control for Documents — Without Git](https://mdflow.cz/blog/version-control-for-documents): What version control for documents means (history, line diffs, restore), why "Git for prose" asks too much of non-engineers, where Google Docs revision history falls short (no portable diff, no real API, not durable), and how MDflow captures version history automatically on every write path — editor, API, and AI agent — with line diffs and one-click restore. Plain-markdown twin: https://mdflow.cz/blog/version-control-for-documents.md
- [The Karpathy-Style Wiki: A Knowledge Base Your AI Maintains](https://mdflow.cz/blog/karpathy-style-wiki): What a Karpathy-style wiki is (a plain-Markdown knowledge base an LLM writes and maintains, not a RAG vector store), where the pattern came from (Andrej Karpathy's April 2026 viral post and "idea file" gist, and its three layers — immutable raw sources, the LLM-maintained wiki, and a schema doc), why an agent-maintained wiki compounds where hand-kept wikis rot, and how to run one with Claude over MDflow's MCP server: folder descriptions as the schema layer, mdflow_get_context for retrieval, and automatic version history as a safety net for every AI edit. Plain-markdown twin: https://mdflow.cz/blog/karpathy-style-wiki.md
- [The Agentic Coding Loop, and the Markdown Memory It Needs](https://mdflow.cz/blog/agentic-coding-loop): What the agentic coding loop is (Andrew Ng's innermost, minutes-long cycle where an AI agent writes, tests, and fixes code against a spec), the developer feedback loop (hours) and external feedback loop (days) nested around it, why agents externalize their spec, plan, and progress to durable markdown, and how MDflow is the shared markdown memory and control surface all three loops turn around — the store agents read and write via MCP and the API, the editor and automatic version history a human steers from, and one workspace many agents coordinate through. Plain-markdown twin: https://mdflow.cz/blog/agentic-coding-loop.md
- [Building for Agents: A Practical Checklist for Developers](https://mdflow.cz/blog/building-for-agents): What it actually means to build a website or web app for AI agents — discovery, content, and operability — and the practical checklist: deliberate robots.txt rules for AI crawlers like GPTBot and ClaudeBot, a curated llms.txt, clean Markdown over JS-only pages, a documented API with token auth, MCP for real operability, GEO and structured data, curated context, and safe write-back. Ties the rest of the series together and shows how MDflow already checks every box. Plain-markdown twin: https://mdflow.cz/blog/building-for-agents.md
- [Developers Are Becoming Builders: What AI Actually Changes](https://mdflow.cz/blog/developers-becoming-builders): An honest, sourced look at the claim that AI is turning developers into "builders" while the rest need a different job — the real role shift (OpenAI's "Delegate, Review, Own", agentic and vibe engineering), what the data actually says about jobs (BLS projects +15% growth through 2034 with AI as a demand driver) and productivity (the METR 19%-slowdown RCT, the perception gap, entry-level compression per Stanford's "Canaries in the Coal Mine"), the skills that separate thrivers (architecture, review discipline, context engineering), and how MDflow's agentic markdown storage — folder descriptions as context, mdflow_get_context, raw .md twins, version history, MCP + API — is the durable memory the builder workflow needs. Plain-markdown twin: https://mdflow.cz/blog/developers-becoming-builders.md
- [MDflow MCP Setup for Cursor, Claude Desktop, and Codex](https://mdflow.cz/blog/mdflow-mcp-setup-cursor-claude-desktop-codex): A step-by-step, per-client setup guide for MDflow's MCP server — create a Personal Access Token, then copy-paste config for Cursor (native Streamable HTTP at https://mdflow.cz/api/mcp), Claude Desktop (the mcp-remote bridge or the local stdio server), Codex (local stdio server, TOML config), and Claude Code (one-line claude mcp add), with remote-vs-local guidance, verification prompts, and a troubleshooting FAQ covering 401/429 errors, missing tools, Node.js on PATH, and how the ChatGPT app connects over OAuth (a custom-connector sign-in) instead of a static token. Plain-markdown twin: https://mdflow.cz/blog/mdflow-mcp-setup-cursor-claude-desktop-codex.md

## API summary

- Base URL: https://mdflow.cz
- Auth: `Authorization: Bearer mdf_...` (Personal Access Token, created at https://mdflow.cz/settings) or an OAuth access token from a Claude/ChatGPT connector
- Rate limit: 60 requests per minute per token and per authenticated user
- `GET /api/v1/workspaces`: List workspaces.
- `POST /api/v1/workspaces`: Create a workspace.
- `PATCH /api/v1/workspaces/{id}`: Rename a workspace or edit its description.
- `DELETE /api/v1/workspaces/{id}`: Delete a workspace and everything inside it.
- `GET /api/v1/folders`: List folders (each with full path); accepts `?workspace_id=`.
- `GET /api/v1/folders/{id}`: Get a folder with its full path and compounded description.
- `POST /api/v1/folders`: Create a folder.
- `PATCH /api/v1/folders/{id}`: Rename, re-describe, or move a folder.
- `DELETE /api/v1/folders/{id}`: Delete a folder and the documents inside it.
- `GET /api/v1/folders/{id}/documents`: List documents in a folder.
- `GET /api/v1/documents`: List all documents (metadata only, no body); accepts `?workspace_id=`.
- `GET /api/v1/documents/{id}`: Get one document, including its markdown body.
- `PATCH /api/v1/documents/{id}`: Rename a document.
- `POST /api/v1/documents`: Create a markdown document in an owned folder.
- `PUT /api/v1/documents/{id}/body`: Replace a document's markdown body.
- `PUT /api/v1/documents/{id}/folder`: Move a document to another folder.
- `PUT /api/v1/documents/{id}/sharing`: Turn public link sharing and comments on or off.
- `GET|POST /api/v1/documents/{id}/shares`: List or add private email shares.
- `DELETE /api/v1/documents/{id}/shares[/{shareId}]`: Revoke all or one private share.

## App

- [MDflow](https://mdflow.cz): The MDflow web app.