Dr. QuantMaster MCP Server
AI-powered quantitative research assistant with 45 tools for causal inference methods (DID, RDD, IV, PSM), regression analysis, power calculations, and statistical code generation in R, Stata, and Python.
README
Dr. QuantMaster MCP Server
AI-Powered Quantitative Research Assistant with 45 MCP tools for causal inference, regression analysis, power calculation, and statistical code generation.
Features
45 MCP Tools in 10 Categories
| Category | Tools | Description |
|---|---|---|
| Knowledge Search | 5 | Search statistical knowledge, method guides, formula lookup |
| Sample Size & Power | 5 | Power analysis, effect size, MDE calculator |
| Diagnostics | 5 | Assumption checks, regression diagnostics, test selection |
| Causal Inference | 6 | DID, RDD, IV, PSM, Synthetic Control guides |
| Code Generation | 8 | R, Stata, Python code generation and optimization |
| Interpretation | 5 | Coefficient interpretation, model fit, results writing |
| Meta-Analysis | 4 | Effect sizes, heterogeneity, publication bias |
| Reporting | 5 | Journal guidelines, APA reporting, preregistration |
| Advanced Methods | 5 | SEM, MLM, Bayesian, ML for causal, time series |
| File Operations | 2 | Analysis file writing, project structure creation |
Causal Inference Methods Supported
- DID (Difference-in-Differences): Parallel trends, staggered adoption, event studies
- RDD (Regression Discontinuity): Sharp/Fuzzy RDD, bandwidth selection, McCrary test
- IV (Instrumental Variables): 2SLS, weak instrument tests, overidentification
- PSM (Propensity Score Matching): Balance diagnostics, caliper selection, ATT/ATE
- Synthetic Control: Donor pool selection, placebo tests, inference
Code Generation
Generate analysis code for:
- R: tidyverse, fixest, did, rdrobust, MatchIt
- Stata: reghdfe, did_imputation, rdrobust, psmatch2
- Python: statsmodels, linearmodels, causalinference
Architecture
Skills (Hot Layer) MCP Tools (Cold Layer) RAG (Vector Search)
| | |
v v v
01_IDENTITY.md 45 Tools 32 ChromaDB Collections
02_CAUSAL_INFERENCE.md - Knowledge Search - stat_foundations
03_REGRESSION.md - Power Analysis - regression_*
- Code Generation - econometrics_*
- Diagnostics - advanced_*
Installation
Prerequisites
- Node.js 18+
- npm or yarn
Setup
# Clone the repository
git clone https://github.com/seanshin0214/quantmaster-mcp-server.git
cd quantmaster-mcp-server
# Install dependencies
npm install
# Build
npm run build
# Copy environment file
cp .env.example .env
Claude Desktop Configuration
Add to claude_desktop_config.json:
Windows:
{
"mcpServers": {
"quantmaster": {
"command": "node",
"args": ["C:\\path\\to\\quantmaster-mcp-server\\dist\\index.js"],
"env": {
"CHROMA_PATH": "C:\\path\\to\\quantmaster-mcp-server\\chroma-data"
}
}
}
}
macOS/Linux:
{
"mcpServers": {
"quantmaster": {
"command": "node",
"args": ["/path/to/quantmaster-mcp-server/dist/index.js"],
"env": {
"CHROMA_PATH": "/path/to/quantmaster-mcp-server/chroma-data"
}
}
}
}
Usage Examples
Power Analysis
Tool: calc_power
Input: { "n": 200, "effectSize": 0.3, "alpha": 0.05 }
Causal Inference Guide
Tool: causal_design_guide
Input: { "method": "did", "context": "policy evaluation" }
Generate R Code
Tool: generate_r_code
Input: {
"method": "did",
"dataDescription": "panel data with treatment in 2020"
}
Interpret Coefficient
Tool: interpret_coefficient
Input: {
"coefficient": 0.15,
"se": 0.05,
"method": "ols",
"outcomeVar": "log_wage"
}
Tool Reference
Knowledge Search Tools
search_stats_knowledge: Search statistical methods databaseget_method_guide: Get detailed method guidesuggest_method: Suggest appropriate method for research questioncompare_methods: Compare two statistical methodsget_formula: Get formula for specific statistic
Power Analysis Tools
calc_sample_size: Calculate required sample sizecalc_power: Calculate statistical powercalc_effect_size: Calculate effect size from statisticsmde_calculator: Calculate minimum detectable effectpower_curve: Generate power curve data
Causal Inference Tools
causal_design_guide: Get causal inference design guideparallel_trends_check: Check parallel trends assumptioniv_strength_check: Check instrument strengthpsm_guide: Propensity score matching guiderdd_bandwidth: RDD bandwidth selection guideevent_study_guide: Event study design guide
Code Generation Tools
generate_r_code: Generate R analysis codegenerate_stata_code: Generate Stata analysis codegenerate_python_code: Generate Python analysis codecode_template: Get code template for methodvisualization_code: Generate visualization codetable_code: Generate publication-ready table codedebug_code: Debug statistical codeoptimize_code: Optimize code performance
32 ChromaDB Collections
| Domain | Collections |
|---|---|
| Foundations | stat_foundations, probability_theory, inference_basics |
| Regression | regression_ols, regression_diagnostics, regression_extensions |
| Econometrics | econometrics_panel, econometrics_iv, econometrics_did, econometrics_rdd |
| Advanced | advanced_sem, advanced_mlm, advanced_bayesian, advanced_ml_causal |
| Meta-Analysis | meta_effect_sizes, meta_heterogeneity, meta_publication_bias |
| Code | code_r, code_stata, code_python |
Skills Files
01_IDENTITY.md
Dr. QuantMaster persona and core capabilities definition.
02_CAUSAL_INFERENCE.md
Detailed guides for DID, RDD, IV, PSM, and Synthetic Control with code templates.
03_REGRESSION.md
OLS, Panel Data, Limited Dependent Variables, Count Models, and Survival Analysis guides.
License
MIT License - See LICENSE for details.
Author
Sean Shin (@seanshin0214)
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Built with Model Context Protocol and ChromaDB
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。