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
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