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TablaCognita logo
Health: ActiveRecent health check succeeded.Last checked 9/22/2026, 8:32:33 PM

TablaCognita

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository2 GitHub StarsTotal stargazers on GitHub for the source repository (2 stars).Visit Website

MCP-native collaborative markdown editor with real-time AI document editing

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for TablaCognita, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
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Documentation Overview

TablaCognita

Co-write with any AI. In your browser. No data on anyone's server.

TablaCognita is a browser-based Markdown editor where AI is a first-class participant, not a feature bolted onto a text box. Select text and send it to your AI. Watch edits land in real time. Undo anything. The AI sees the document through MCP tools β€” the same protocol that powers Claude Desktop, Cursor, and every other MCP-capable client.

Your document lives in your browser. The relay server is a stateless wire. Nobody stores your writing.

How It Works

Code
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”   MCP (stdio | HTTP)   β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”   WebSocket   β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  Your AI     │◄───────────────────────►│    Relay      │◄────────────►│  Browser Editor   β”‚
β”‚  (Claude,    β”‚   Tool calls/results    β”‚  (stateless)  β”‚              β”‚  (source of truth)β”‚
β”‚   Cursor,    β”‚                         β”‚               β”‚              β”‚                   β”‚
β”‚   any MCP)   β”‚                         β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜              β”‚  CodeMirror 6     β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜                                                       β”‚  Live preview     β”‚
                                                                       β”‚  Section tracking β”‚
                                                                       β”‚  Lock management  β”‚
                                                                       β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

The AI reads and writes through 17 MCP tools. The editor handles section addressing, fuzzy text matching, collision avoidance, and undo. The relay just passes messages. That's it.

Quick Start

bash
git clone https://github.com/pstryder/tablacognita.git
cd tablacognita
npm install
npm start

Open http://localhost:3000 in your browser. The editor is live.

Connect your MCP client. For Claude Desktop, add to your config:

config.json
{
  "mcpServers": {
    "tabla-cognita": {
      "command": "node",
      "args": ["server/index.js", "--transport", "stdio"],
      "cwd": "/path/to/tablacognita"
    }
  }
}

Your AI can now read your document, edit sections, replace text, and respond to selections you send it from the editor.

What Your AI Can Do

Read β€” read_document, get_structure, get_section. The AI sees your full document, section outline, or individual sections by heading name or stable ID.

Write β€” replace_section, replace_text, insert_after, append. Section-level edits with auto-locking. Fuzzy text matching that works through markdown formatting (**bold text** matched by searching "bold text"). Full document replacement requires your confirmation in the browser.

Coordinate β€” request_edit_lock, release_lock, get_cursor_context, get_dirty_regions, poll_context. The AI knows where your cursor is, which sections you've edited since it last looked, and can lock sections for multi-step operations. All locks have TTLs β€” nothing stays locked forever.

Manage β€” open_document, snapshot, restore_snapshot, get_revision_history. Named checkpoints saved to your browser's IndexedDB. Restore any snapshot with one tool call.

Key Design Decisions

Browser is source of truth. The relay holds zero document state. If the relay restarts, your document is still in your browser. The AI reconnects and continues.

Section IDs are stable. Rename a heading from "Introduction" to "Overview" β€” the section ID doesn't change. The AI can always find its way back.

Agent edits are undoable. Every AI edit goes through CodeMirror's transaction system. Ctrl+Z works on AI edits exactly like your own.

Locks are intent signals, not mutexes. Auto-locks during edits are atomic and invisible. Explicit locks for multi-step operations have TTLs and never block you β€” just a gentle indicator that the AI is working on a section.

Notifications are fire-and-forget. The editor tells the AI when you move between sections, rename headings, or delete content. If the transport doesn't support notifications, the AI can poll instead. No feature depends on notifications arriving.

No data leaves your browser. Documents live in CodeMirror's state. Snapshots live in IndexedDB. The relay is a WebSocket bridge with no storage. There is nothing to subpoena.

Project Structure

Code
server/
  index.js          β€” MCP server + Express + WebSocket relay
  relay.js          β€” WebSocket relay, request/response correlation
  sessions.js       β€” Session management
  tools.js          β€” MCP tool definitions and handlers

editor/
  index.html        β€” Editor shell with CodeMirror 6 via ESM CDN
  app.js            β€” Editor logic, WebSocket handlers, all tool implementations
  styles.css        β€” Dark theme

shared/
  protocol.js       β€” Message types, error codes, constants
  sections.js       β€” Section parser with stable ID registry
  fuzzy.js          β€” 4-level fuzzy matching cascade
  locks.js          β€” Lock state machine with TTL
  notifications.js  β€” Notification debouncing and validation

test/
  relay.test.js     β€” Full relay round-trip tests
  sections.test.js  β€” Section parser unit tests
  fuzzy.test.js     β€” Fuzzy matching unit tests
  locks.test.js     β€” Lock state machine tests
  notifications.test.js β€” Notification system tests
  mock-browser.js   β€” Mock WebSocket client for automated testing

Running Tests

Terminal
npm test              # All 122 tests
npm run test:sections # Section parser only
npm run test:fuzzy    # Fuzzy matching only
npm run test:relay    # Relay round-trip only

Transport Modes

Terminal
npm start                    # HTTP transport (default, port 3000)
npm run start:stdio          # stdio transport (for local MCP clients)
npm start -- --port 8080     # Custom port

Requirements

  • Node.js 18+
  • A modern browser
  • Any MCP-capable AI client

Architecture Details

See DESIGN.md for the full specification: tool contracts, WebSocket protocol, invariants, failure modes, and build plan.

License

Apache 2.0

Credits

TablaCognita was designed and built by Pete Marchetti (PStryder) at Technomancy Laboratories, with architectural review and first live edit by Kee (Claude Opus 4.6).

The page that knows. β€” tabla cognita

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
2
Stargazers on the source repository.
Last commit
6mo ago
Most recent push to the default branch.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about TablaCognita

We don't have a confirmed install command for TablaCognita yet, so we don't publish a generated one β€” a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/PStryder/TablaCognita) for the current steps.

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Technical Specs & Signals

Category🏒Workplace & Productivity
More technical detailsExpand β–Ύ
Last updatedMar 5, 2026
3/7 checks healthy over the last 45d
Views0
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Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars2
GitHub Star CountTotal stargazers on GitHub representing community popularity (2 stars).
Last commit6mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Mar 5, 2026
29Quality signal: Emerging Β· 29/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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