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Tdcv2

by NickLiapinversion 0.1.7i★ –iRuns on your computer
Registry nameio.github.NickLiapin/tdcv2

Install

Overview

Description from the maker (original English)

Fake, mock and test data generator: CSV, JSON, SQL from a .tdc config, made locally by TDCv2.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Databases & datasets

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "tdcv2": {
      "command": "npx",
      "args": [
        "-y",
        "tdcv2-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add tdcv2 -- npx -y tdcv2-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "tdcv2": {
      "command": "npx",
      "args": [
        "-y",
        "tdcv2-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "tdcv2": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "tdcv2-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account NickLiapin, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Databases & datasetsi

  • More stars than 0% of the other 1135 servers in this category
  • Published to the registry more recently than 92% of the other 1135 servers in this category
  • Basic checks equal to or better than 100% of the other 1135 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Tdcv2 safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.7) reached the registry 3 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Supabase

by supabase

Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.

Computer or cloud★ 2,993Apache-2.0Updated yesterday
Install

MongoDB MCP Server

by mongodb-js

MongoDB Model Context Protocol Server

Runs on your computer★ 1,157Apache-2.0Updated 3 days ago
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

TDCv2 for AI agents

A data generator for your coding agent: fake, mock, synthetic and test data with TDCv2 — realistic names, emails, addresses, phone numbers, IBANs and more. The agent writes a small .tdc config, the TDCv2 engine generates the rows on your machine, and the same config gives the same file, byte for byte, every time you run it. CSV, JSON, SQL inserts or any text format; fields that agree with each other; exact shares; related tables; data packs for 95 languages and 198 countries. Think Faker, but for whole datasets: database seeds, test fixtures, demo data.

Two parts, one version:

  • a skill — teaches the agent the TDC language, the workflow and the traps (skills/tdcv2);
  • an MCP server, tdcv2-mcp — the same, as tools: check a config, generate, find and install data packs, summarise a file, read the docs (mcp/).

Install

Claude Code and Cowork — the plugin brings both the skill and the server. The simplest way: in claude.ai or the Claude app, Customize → Plugins → Discover, find TDCv2 — Fake & Test Data Generator, Add; Claude Code picks it up at the next session and keeps it updated. Or from this repository's marketplace:

claude plugin marketplace add NickLiapin/tdcv2-agents

claude plugin install tdcv2@tdcv2

Install one way, not both — otherwise the skill loads twice and two servers start.

Codex, Copilot, Gemini CLI, Cursor and other agents that read skills — put the skill where your agent looks for it:

npx -y tdcv2-mcp@0.1.7 install-skill            # ~/.claude/skills/tdcv2

npx -y tdcv2-mcp@0.1.7 install-skill --agents # ~/.agents/skills/tdcv2 npx -y tdcv2-mcp@0.1.7 install-skill --project # ./.claude/skills/tdcv2 npx -y tdcv2-mcp@0.1.7 install-skill --dir

Any MCP client (Claude Desktop, Cursor, VS Code…):

{ "mcpServers": { "tdcv2": { "command": "npx", "args": ["-y", "tdcv2-mcp@0.1.7"] } } }

Claude Desktop starts servers in /: add "env": {"TDCV2_PROJECT": "/path/to/project"} to that entry so the files have a folder to go to. On Windows use "command": "npx.cmd" if the client cannot start npx. Everything needs Node.js 20 or newer.

Step by step for each agent and client: TDC for AI agents.

Then ask in plain words — *"500 customers from 20 countries as CSV"*, *"a pytest test for validate_user on 50 different users"* — and the agent takes it from there: writes the config, checks it with the engine, generates, and hands you the file together with the config that reproduces it.

Privacy

The engine runs locally. Neither the skill nor the server sends your data or your configs anywhere. The server reads .tdc files and writes generated files only inside the project folder it is started in.

Network access, all of it:

  • the plugin starts the server with npx -y tdcv2-mcp@0.1.7, its own version (scripts/mcp-launch.mjs), so the first start downloads that exact version and its dependencies, the TDCv2 engine among them, from the npm registry;
  • npx -y tdcv2-mcp@0.1.7 … in the commands above does the same, and so does npx -y tdcv2@0.3.7 …, the exact engine version the agent runs;
  • with an engine of another version, the agent may read that version's doc page from raw.githubusercontent.com;
  • data packs are downloaded only when you or the agent run tdcv2 pack add (through the server: tdc_pack_add, which your client asks you to allow);
  • a config with sends the named values to that URL — only if someone writes such a config.

Nothing else is fetched, and nothing is sent. The full policy: PRIVACY.md.

Versions

This release, 0.1.7, is checked against TDCv2 0.3.7. The skill's reference is built from the engine's documentation for that version; with another engine version the agent reads that version's pages, and the engine's own check has the last word.

License

MIT

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