Generate-Data

io.github.ns-3ePublished by GitHub account ns-3ev2.0.1Updated Oct 24, 2026

MCP server for Generate-Data.com: dataset generation, AI schema design, Project management.

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Overview

AI-generated overview

A local MCP server that lets an assistant generate synthetic datasets, design schemas from plain English, and manage Generate-Data.com Projects.

What you can do
Generate synthetic dataset rows from a field list in CSV, JSON, XML, Parquet or ZIP, with binary formats returned base64-encoded and row/column limits set by the API key tier. Design a dataset schema from a natural-language prompt, or refine an existing schema by passing the conversation and current schema. Browse available field types by category and look up the configuration options for a single field type. Check API key usage: calls today, tier and limits. List the user's Projects with pagination and generate all tables in a Project, downloading the result.
When to use it
Useful when you need realistic fake or test data for demos, fixtures or development, or want an assistant to turn a plain-English description into a dataset schema and then produce the rows without leaving the chat.
Requirements
Runs locally over stdio, typically launched with uvx or installed via pip. Requires a Generate-Data.com account and an API key supplied in the GENERATE_DATA_API_KEY environment variable; the optional GENERATE_DATA_API_BASE_URL overrides the API endpoint. Network access to the Generate-Data.com API is needed. Premium tools require a Premium-tier key.
Before you install
The API key is a secret and the README warns against committing config files containing it. Generation is billed or limited by tier: Free keys allow 100 rows, 10 columns, CSV only and 10 calls per day, while Premium raises these to 100,000 rows, 50 columns, more formats and 1,000 calls per day. Dataset prompts and schemas are sent to the Generate-Data.com API. Project generation downloads generated data.

Installation

In SourceWeft

  1. Open Generate-Data in the dashboard and add it to a workspace.
  2. 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

generate-data-mcp

[PyPI]

An MCP server for Generate-Data.com — generate synthetic datasets, design schemas from natural language, and manage Projects, straight from your agent.

Thin HTTP wrapper over the Generate-Data.com API. No generation logic lives in this repo — it's a curated, agent-friendly interface onto the real thing: 7 tools, one consistent response shape, binary-safe output, and server-side validation on every input.

Installation (30-second setup)

You need a Generate-Data.com API key first — create one in Settings → API Access on generate-data.com.

Claude Desktop / Cursor (recommended)

Add this to your MCP client config (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json):

json
{  "mcpServers": {    "generate-data": {      "command": "uvx",      "args": ["generate-data-mcp"],      "env": {        "GENERATE_DATA_API_KEY": "your-uuid-key-here"      }    }  }}

uvx fetches and runs the latest published version on demand — no separate install step, nothing to update by hand. Restart your client and the 7 gd_* tools are available.

Do not commit a config file containing your real API key.

uv / uvx (any MCP client)
bash
# run once, ad hoc:uvx generate-data-mcp
# or install it as a persistent CLI tool:uv tool install generate-data-mcp
pip (fallback)
bash
pip install generate-data-mcp

For local development against this repo directly:

bash
git clone https://github.com/ns-3e/generate-data-mcp.gitcd generate-data-mcppip install -e ".[dev]"

Verify it works

bash
export GENERATE_DATA_API_KEY=your-keygenerate-data-mcp

From your MCP client, invoke gd_get_usage — it should return your tier and call counts. Then invoke gd_list_field_types — it should return the category map.

Bam — you're ready to generate data.

Ask your agent something like "generate 50 rows of fake e-commerce customers as CSV" and it will call gd_design_schema then gd_generate_dataset on its own.

Quick start

A typical session looks like this — the agent chains tools on its own, you just describe the outcome:

  1. Discover what's possible. gd_list_field_types — see every field type, grouped by category.
  2. Design a schema. gd_design_schema(prompt="E-commerce customers with name, email, and signup date") — proposes a fields array from plain English.
  3. Generate the data. gd_generate_dataset(fields=..., num_rows=10, format="csv") — returns the rows.
  4. Refine if needed. Call gd_design_schema again, this time passing messages (the running conversation) + current_schema (the prior result) together — it refines instead of proposing fresh.

Every tool returns the same envelope: {"ok": true, "summary": "...", "data": {...}} on success, or {"ok": false, "error": {"code": ..., "message": ...}} on failure — errors always tell you what to do next, never a raw stack trace.

Local development

json
{  "env": { "GENERATE_DATA_API_BASE_URL": "http://localhost:8000" }}

Point at a locally running Django backend instead of the hosted API.

Migrating from v1

v2.0.0 renames every tool (breaking change). Old name → new name:

  • generate_data → gd_generate_dataset
  • list_field_types → gd_list_field_types
  • get_field_options → gd_get_field_type_options
  • propose_schema → gd_design_schema (first call, no messages/current_schema)
  • refine_schema → gd_design_schema (pass messages + current_schema together)
  • get_api_usage → gd_get_usage
  • list_projects → gd_list_projects (now paginated: limit/offset)
  • generate_project → gd_generate_project (binary formats now returned base64-encoded, not corrupted utf-8)

Reference

All 7 tools, split by tier.

Free tier

  • gd_generate_dataset — Generate synthetic dataset rows from a field list. format: csv, json, xml, parquet, or zip (binary formats return base64-encoded).
  • gd_list_field_types — List all available field types grouped by category. Takes no arguments.
  • gd_get_field_type_options — Get the configuration option schema for one field type. field_type must match ^[a-z0-9_]+$.
  • gd_design_schema — Design a dataset schema from natural language, or refine an existing one — one tool for both the first proposal and follow-up conversation turns.
  • gd_get_usage — Get current API key usage stats: calls today, tier, limits. Takes no arguments.

Premium tier

Requires a Premium API key — Free-tier keys get a tier_forbidden error.

  • gd_list_projects — List the user's Projects, paginated (limit/offset, default 20/0).
  • gd_generate_project — Generate all tables in a Project and download the result. Same format/binary rules as gd_generate_dataset.

Tier limits (API key)

CapabilityFreePremium
Max rows / request100100,000
Max columns1050
FormatsCSVCSV, JSON, XML, Parquet
Daily API calls101,000

Limits are enforced by the Django API, not this MCP server.

Configuration

VariableRequiredDefault
GENERATE_DATA_API_KEYYes—
GENERATE_DATA_API_BASE_URLNohttps://api.generate-data.com

Troubleshooting

SymptomFix
GENERATE_DATA_API_KEY is requiredSet env var before starting the server
HTTP 401 / auth_failedInvalid or deactivated key
HTTP 429 / rate_limitedPer-minute or daily cap hit; wait or upgrade tier
HTTP 403 / tier_forbiddenFree tier lacks access; upgrade plan
unsupported_formatformat must be one of csv, json, xml, parquet, zip
invalid_input on a field type or project IDValue failed server-side validation before any request was sent — check spelling/type

Development

bash
git clone https://github.com/ns-3e/generate-data-mcp.gitcd generate-data-mcppip install -e ".[dev]"pytest tests/ -v

API docs

Docs live on generate-data.com. See this repo's tool docstrings (generate_data_mcp/server.py) for the authoritative request/response shapes.

Source: README.md at commit b10ee5b

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v2.0.1LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

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  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts