spss-studio-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@spss-studio-mcp用 examples/data/survey_study.sav 做描述统计和可靠性分析"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SPSS Studio MCP
让 SPSS 成为 Agent 的「统计引擎 + 制图工厂」:论文级图片、深度结果解析、方法真机验证、安全执行。
spss-studio-mcp 是一个面向 IBM SPSS Statistics 的 MCP(Model Context
Protocol)服务器,为 Codex / Claude Code / Cursor 等 Agent 客户端提供:
论文级出图:11 类
spss_chart_*工具,一键导出 PNG / TIFF / EMF(1950×1500 @300 dpi),路径回传可直接投稿;深度结果解析:OMS 文本 → Markdown 表格 + 结构化 JSON + 16 类分析统计摘要(t / F / r / B / Wald / α / χ² / p / 效应量);
方法真机验证:37 个分析方法 + 11 个补充工具全部在真实 SPSS 32 验收通过;
中介 / 调节:
spss_mediation(Baron & Kenny 三步回归 + Sobel)、spss_moderation(中心化交互回归);安全执行层:危险命令拦截、数据路径白名单、
dry_run预检、JSONL 审计日志。
全部能力已在 IBM SPSS Statistics 32.0.0(Windows) 真机验证(109 个单元测试全部通过)。
快速开始
cd spss-studio-mcp
pip install -e ".[dev]"
spss-studio-mcp status # 应显示 SPSS batch: OK
spss-studio-mcp configure-codex # 写入 Codex 客户端配置(~/.codex/config.toml)
spss-studio-mcp configure-claude # 写入 Claude Code 配置(~/.claude.json)然后在客户端里直接用自然语言驱动,例如:
对 examples/data/survey_study.sav 做描述统计和可靠性分析
用 examples/data/experiment_study.sav 做独立样本 t 检验(group 分组,posttest)
用 examples/data/mediation_study.sav 做中介分析:autonomy → satisfaction → performance
画 examples/data/survey_study.sav 学习投入总分的直方图(带正态密度),PNG 300dpiRelated MCP server: Stata MCP Server
论文级图表(核心卖点)
工具 | 用途 |
| 分布直方图 / 直方图 + 正态密度 |
| 两变量散点图 |
| 分类均值条形 / 条形 + 95% CI 误差须 |
| 时间序列折线 / 面积图 |
| 分组箱线图 |
| 均值 ± CI 误差条 |
| 正态 Q-Q 图 |
| Kaplan-Meier 生存曲线 |
spss_chart_histogram_density(
variable="engagement_total",
title="学习投入总分分布(带正态密度)",
image_format="PNG", # PNG / TIFF / EMF
width_px=1950, height_px=1500, dpi=300,
data_file="examples/data/survey_study.sav",
)
# → 返回图片文件路径,可直接投稿样例输出(SPSS 32 真机导出,1950×1500 @300 dpi):

结构化结果与统计摘要
spss_structured_result(
syntax="T-TEST GROUPS=group(1 2) /VARIABLES=posttest.",
data_file="examples/data/experiment_study.sav",
)
# → {markdown, json: {tables, summary}, files, warnings}run_syntax 返回的 Markdown 末尾自动附加 ### 统计摘要(自然语言结论 + 关键统计量),
16 类分析的摘要抽取细节见 docs/result_parsing.md。
样例数据
examples/data/ 提供 5 组贴近论文场景的样例数据(固定随机种子,可复现):
文件 | 场景 | 关键变量 |
| 问卷:200 人学习投入 |
|
| 实验:120 人记忆训练前后测 |
|
| 生存:150 例随访 |
|
| 中介:300 员工 |
|
| 纵向:60 人 3 次测量 |
|
安全执行
危险命令(
HOST/ERASE/DELETE FILE等)行首匹配拦截;数据文件路径白名单(
SPSS_ALLOWED_DIRS,默认examples/+ 系统临时目录);spss_run_syntax(..., dry_run=True)先校验不执行;审计日志默认写入
logs/audit.jsonl(可用SPSS_AUDIT_LOG改路径)。
详见 docs/security.md。
文档
生态收录与发布
状态:P0–P4 里程碑完成,v1.0.0 发布准备就绪;
LobeHub / PulseMCP 收录条目与提交清单:docs/ecosystem.md;
Release v1.0.0 说明:docs/release_notes_v1.0.md。
许可证
MIT(上游:Exekiel179/SPSS-MCP,MIT)。
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