MCP工具中文文档 — MCP工具 | AI评分 8.0

能力标签

🔌 MCP 🤖 Agent 🔄 工作流 💻 CLI 🧠 Claude ✨ GPT

🔌

MCP工具

基于 Python · 让 AI 助手直接操作你的系统与工具

英文名：stata-code

⭐ 10 Stars 🍴 2 Forks 💻 Python 📄 MIT 🏷 AI 8.0分

8.0AI 综合评分

mcp数据分析python

⬇ 下载源码 ZIP ⚙️ 配置说明 📺 TG 频道

✦ AI Skill Hub 推荐

MCP工具是 AI Skill Hub 本期精选MCP工具之一。综合评分 8.0 分，整体质量较高。我们强烈推荐将其纳入你的 AI 工具库，帮助提升工作效率。

📚 深度解析

MCP工具是一款基于 MCP（Model Context Protocol）标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源，旨在建立 AI 模型与外部工具之间的标准化通信接口，目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 MCP工具，你的 AI 助手将获得额外的工具调用能力，可以用自然语言直接操控该工具的功能，无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置，永久增强"——配置完成后，每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上，MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信，工具的功能以"工具列表"的形式暴露给 AI 模型，AI 可以按需调用。MCP工具提供了结构化的工具调用接口，使 AI 模型能够精确地理解和使用每个功能点，显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比，MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON，即可让 AI 获得全新能力。AI Skill Hub 将 MCP工具评为 AI 评分 8.0 分，属于同类工具中的优质选择。

📋 工具概览

MCP工具是一款遵循 MCP（Model Context Protocol）标准协议的 AI 工具扩展。通过 MCP 协议，它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务，实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用，都可以通过自然语言在 AI 对话中直接触发，极大提升生产效率。

GitHub Stars

⭐ 10

开发语言

Python

支持平台

Windows / macOS / Linux

维护状态

轻量级项目，按需更新

开源协议

MIT

AI 综合评分

8.0 分

工具类型

MCP工具

Forks

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理，如需查看完整原始文档请访问底部「原始来源」。

📌 核心特色

通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
提供结构化工具调用接口，显著降低 AI 集成复杂度
支持 Claude Desktop 和 Claude Code 无缝接入，开箱即用
可与其他 MCP 工具组合叠加，构建完整 AI 工作站
轻量无侵入设计，不影响现有系统架构

🎯 主要使用场景

在 Claude Desktop 对话中直接调用本地工具，实现 AI 与系统的深度联动
通过自然语言驱动复杂的多步骤自动化任务，代替繁琐手动操作
将多个 MCP 工具组合使用，构建个人专属 AI 工作站

以下安装命令基于项目开发语言和类型自动生成，实际以官方 README 为准。

安装命令

# 方式一：通过 Claude Code CLI 一键安装
claude skill install https://github.com/brycewang-stanford/stata-code

# 方式二：手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "mcp--": {
      "command": "npx",
      "args": ["-y", "stata-code"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json

📋 安装步骤说明

确认已安装 Node.js（v18 或以上版本）
打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
保存配置文件并重启 Claude 客户端
重启后，在对话中即可使用本工具

以下用法示例由 AI Skill Hub 整理，涵盖最常见的使用场景。

常用命令 / 代码示例

# 安装后在 Claude 对话中直接使用
# 示例：
用户: 请帮我用 MCP工具 执行以下任务...
Claude: [自动调用 MCP工具 MCP 工具处理请求]

# 查看可用工具列表
# 在 Claude 中输入："列出所有可用的 MCP 工具"

以下配置示例基于典型使用场景生成，具体参数请参照官方文档调整。

配置示例

// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "mcp__": {
      "command": "npx",
      "args": ["-y", "stata-code"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效

📑 README 深度解析真实文档完整度 49/100 查看 GitHub 原文 →

以下内容由系统直接从 GitHub README 解析整理，保留代码块、表格与列表结构。

简介

<a href="README.md">English</a> | <a href="README.zh.md">中文</a>

Install

Requirements: Stata 17+ (with pystata shipped by Stata) and Python 3.10+.

```bash

or from source (editable install for development)

git clone https://github.com/brycewang-stanford/stata-code.git cd stata-code pip install -e ".[mcp,kernel]"


> **Naming note.** The PyPI distribution is `stata-code` (hyphen), but
> the Python import is `stata_code` (underscore — Python identifiers
> can't contain hyphens). Same convention as `scikit-learn` →
> `import sklearn`. So: `pip install stata-code`,
> `from stata_code import run`.

Note: `pystata` is **not** on PyPI; it ships with Stata. `stata-code` auto-discovers it on macOS at `/Applications/Stata/utilities/pystata` and at equivalent Linux / Windows paths. If your install is elsewhere, add it to `PYTHONPATH` before importing.

Verify the local setup with the read-only doctor:

bash stata-code doctor stata-code doctor --json # machine-readable output stata-code doctor --no-stata-probe # skip live Stata initialization ```

The doctor reports the package/Python version, MCP and Jupyter extras, pystata discovery, console scripts on PATH, client/VS Code configuration hints, and a best-effort Stata version/edition probe. It never edits shell, Stata, Claude, or VS Code config.

---

user scope — install once, available in every Claude Code workspace on this machine

claude mcp add stata-code --scope user -- stata-code-mcp

1. Install stata-code with the kernel extra (pulls in ipykernel)

pip install "stata-code[kernel]"

python -m stata_code.kernel install --user


Verify the kernel is registered:

bash jupyter kernelspec list

Quick Start

See examples/ for end-to-end cookbook entries: basic regression, DiD, graphs, multi-session, and large matrices.

local scope — only for the current workspace (your local Claude config, not committed)

claude mcp add stata-code --scope local -- stata-code-mcp

As a VS Code Extension

The companion extension is on the Marketplace as brycewang-stanford.stata-code-vscode. It spawns stata-code-mcp as a child process and adds syntax highlighting, an Outline view for **# sections and program define blocks, code-lens "Run cell" and "Run section" actions on .do files, a seven-view sidebar (sessions / last result / data variables / run history / logs / graphs / outputs) — including an agent-native equivalent of Stata's Variables window and an Outputs panel that surfaces the esttab tables and export files each run writes to disk — status-bar indicators, completions, help lookup, conservative variable rename, and inline diagnostics from the v1.0 typed errors.

```bash

from the VS Code CLI

code --install-extension brycewang-stanford.stata-code-vscode ```

Or open the Extensions sidebar in VS Code and search stata-code. The extension is also available from Open VSX so Cursor, Windsurf, and other VS Code-compatible editors can install it without going through the Microsoft Marketplace.

On first activation the extension probes for stata-code-mcp on PATH (and in any workspace .venv / venv). If nothing resolves, it shows a one-time install hint with the exact pip install "stata-code[mcp]" command — choose Don't show again to silence it for the installed extension version.

If the extension or an MCP client cannot find the server, run stata-code doctor --no-stata-probe in the same Python environment. It reports whether stata-code-mcp is on PATH and suggests absolute-path or python -m stata_code.mcp fallbacks for GUI clients whose PATH differs from your shell.

Cell and section conventions

The extension recognizes two complementary structural markers inside .do files. Either can be mixed in the same file; they do not conflict.

Marker	Purpose	Example
`* %% [title]`	Cell boundary. Each marker gets a ▶ Run Cell code-lens; "Run Cell" submits the lines between this marker and the next one. Compatible with the Jupyter-style cell convention used by `kylebutts/vscode-stata`.	`* %% 02 model fit`
`# title` … `###### title`	Section heading, 1–6 levels deep. Each heading gets a ▶ Run Section code-lens and contributes to the Outline view. "Run Section" submits the heading through the next equal- or higher-level heading, matching the hierarchical execution model from `ZihaoVistonWang.stata-all-in-one`.	`**## DiD specification`

program define … end blocks are also surfaced in the Outline, nested under whichever section contains them.

The extension still requires the MCP extra on your system Python (pip install "stata-code[mcp]"), so that stata-code-mcp resolves on PATH and can import the MCP SDK. Stata 17+ and a valid Stata license are required as for any other frontend.

---

Comparison

	stata-code	SepineTam/stata-mcp	hanlulong/stata-mcp	nbstata
License	MIT	AGPL-3.0	MIT	GPL-3.0
Standalone MCP	✓	✓	bundled with VS Code	—
Jupyter kernel	✓	—	—	✓
Unified result schema	✓ ([SCHEMA.md](SCHEMA.md))	per-tool	per-tool	per-tool
Token-economy defaults	✓ (log refs, graph refs)	—	—	—
Typed errors + suggestions	✓ (31 kinds)	—	—	—
Multi-session	✓ (Stata frames)	partial	—	—
Mature ecosystem	early	✓ (statamcp.com, cookbook)	✓ (11k installs)	✓

stata-code is the younger, MIT-licensed, agent-native alternative in this problem space. Among the AGPL options, SepineTam's stata-mcp is currently more mature; stata-code is aimed at cases where copyleft contagion is unacceptable and agents need structured results.

---

🎯 aiskill88 AI 点评 A 级 2026-06-21

高质量的MCP工具，易于使用