Generate-Data

io.github.ns-3e由 GitHub 账号 ns-3e 发布v2.0.1更新于 Oct 24, 2026

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

已验证STDIO仅桌面开发者工具数据与分析

概览

AI 生成的概览

一个本地 MCP 服务器,让助手生成合成数据集、用自然语言设计数据结构,并管理 Generate-Data.com 项目。

可以做什么
按字段列表生成合成数据行,支持 CSV、JSON、XML、Parquet 和 ZIP,二进制格式以 base64 返回,行数与列数上限由 API 密钥等级决定。根据自然语言提示设计数据集结构,或传入对话与当前结构来改进已有结构。按类别浏览可用字段类型,并查询单个字段类型的配置选项。查看 API 密钥用量:当日调用次数、等级和限额。分页列出用户的项目,并生成项目中的所有表并下载结果。
适用场景
适合需要为演示、测试数据或开发准备逼真的假数据时使用,也适合让助手把一段自然语言描述转成数据集结构并直接产出数据行,无需离开对话。
运行要求
通过 stdio 在本地运行,通常用 uvx 启动或通过 pip 安装。需要 Generate-Data.com 账户,并在 GENERATE_DATA_API_KEY 环境变量中提供 API 密钥;可选的 GENERATE_DATA_API_BASE_URL 可覆盖 API 地址。需要能访问 Generate-Data.com API 的网络。高级工具需要 Premium 等级的密钥。
安装前请注意
API 密钥属于机密,README 提醒不要提交包含真实密钥的配置文件。生成受等级限制:免费密钥仅支持 100 行、10 列、仅 CSV、每天 10 次调用;Premium 提升到 100,000 行、50 列、更多格式和每天 1,000 次调用。数据集提示和结构会发送到 Generate-Data.com API。生成项目会下载生成的数据。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Generate-Data,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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.

来源:README.md,提交 b10ee5b

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v2.0.1最新Sep 16, 2026

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