GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Turn key: value notes, CSV/TSV and Markdown tables into typed JSON. Plain code, no AI, runs locally.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"json-shaper-lite": {
"command": "uvx",
"args": [
"json-shaper-lite",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add json-shaper-lite -- uvx json-shaper-lite mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"json-shaper-lite": {
"command": "uvx",
"args": [
"json-shaper-lite",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"json-shaper-lite": {
"type": "stdio",
"command": "uvx",
"args": [
"json-shaper-lite",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 tidybytetools 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.1.0)于3天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Free tool that turns key: value notes, CSV/TSV and Markdown tables into clean JSON. Need app logs or US addresses parsed too? The paid version does that: [json-shaper on Gumroad](https://tidybyte.gumroad.com/l/cznmeo)
Plain code, not AI, so the same text always gives the same JSON. Runs on your own computer. MIT license. Works with Python 3.10 and newer, on Windows, Mac and Linux.
pip install json-shaper-lite
Or use pipx, which keeps it in its own space:
pipx install json-shaper-lite
Want the newest code from GitHub instead?
pip install git+https://github.com/tidybytetools/json-shaper-lite
Or just download json_shaper_lite.py and run it with python3. That one file uses only Python's standard library. (Installing with pip also adds the mcp package, which the MCP server needs.)
printf 'Name: Ada\nAge: 36\nActive: yes' | json-shaper-lite
json-shaper-lite export.csv json-shaper-lite notes.md --format markdown json-shaper-lite export.csv --json # {"ok": true, "format": "csv", "data": [...]}
Output:
{"name": "Ada", "age": 36, "active": true}
Numbers come out as numbers, yes/no and true/false as booleans, and empty or "null" as null. The format is detected for you, or you can set it with --format kv|csv|markdown.
From Python:
from json_shaper_lite import shape
shape("x,y\n1,2") # {'format': 'csv', 'data': [{'x': 1, 'y': 2}]}
When you run it in a terminal it prints one short line about the paid version to stderr after the result. It never goes into your JSON output, it only shows when you are looking at a terminal, and --quiet turns it off.
007 or a zip code can turn into a number. Fix those by hand after.| json-shaper-lite | flatten-json | csvkit csvjson | pandas | |
|---|---|---|---|---|
| Main job | messy text → JSON | nested JSON → flat (and back) | CSV → JSON | full data toolkit |
| Install size | one file (pip adds mcp for the MCP server) | small | medium | large |
key: value notes | yes | no | no | no |
| Markdown tables | yes | no | no | no, not built in |
| CSV/TSV | yes | no | yes | yes |
| Guesses numbers and true/false | yes | no | yes | yes |
| Nested JSON flatten/unflatten | no | yes | no | yes (json_normalize) |
| MCP server for AI apps | yes | no | no | no |
If your data is already JSON and just too nested, flatten-json is the better pick.
There is a small free MCP server built in. It gives your AI app two tools. Both only read. They never write or change files, and they never use the internet. It needs uv.
Run it by hand to check it starts (it waits quietly for an app to talk to it):
uvx json-shaper-lite mcp
Claude Desktop (claude_desktop_config.json) or Cursor (~/.cursor/mcp.json):
{
"mcpServers": { "json-shaper-lite": { "command": "uvx", "args": ["json-shaper-lite", "mcp"] } } }
uvx --from json-shaper-lite json-shaper-lite-mcp starts the same server.
Tools:
shape_text_to_json(text, format="auto"): for text in the chat.shape_file_to_json(path, format="auto"): for a text file on your computer (.txt, .csv, .tsv, .md, up to 5 MB).Both return {"format": "csv", "data": [...]}. format can be auto, kv, csv or markdown.
key: value lines, CSV/TSV, or a Markdown table and need typed JSON.--format kv|csv|markdown.uvx json-shaper-lite mcp gives two read-only tools, shape_text_to_json and shape_file_to_json.--json, one object: {"ok": true, "format": "csv", "data": [...]}. On error ok is false. Exit code 0 ok, 1 error.llms.txt.| lite (free) | json-shaper | |
|---|---|---|
| key: value notes, CSV/TSV, Markdown tables | yes | yes |
| App logs (timestamp, level, message, key=value fields) | no | yes |
| One-line US address splitter | no | yes |
tool.json manifest for scripts and AI agents | no | yes |
pip install "mcp>=1.10,<2"
python3 -m unittest discover tests
The MCP tests are skipped if mcp is not installed.
MIT. See LICENSE.