README.md•6.34 kB
# 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
```bash
# 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:**
```json
{
"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:**
```json
{
"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 database
- `get_method_guide`: Get detailed method guide
- `suggest_method`: Suggest appropriate method for research question
- `compare_methods`: Compare two statistical methods
- `get_formula`: Get formula for specific statistic
### Power Analysis Tools
- `calc_sample_size`: Calculate required sample size
- `calc_power`: Calculate statistical power
- `calc_effect_size`: Calculate effect size from statistics
- `mde_calculator`: Calculate minimum detectable effect
- `power_curve`: Generate power curve data
### Causal Inference Tools
- `causal_design_guide`: Get causal inference design guide
- `parallel_trends_check`: Check parallel trends assumption
- `iv_strength_check`: Check instrument strength
- `psm_guide`: Propensity score matching guide
- `rdd_bandwidth`: RDD bandwidth selection guide
- `event_study_guide`: Event study design guide
### Code Generation Tools
- `generate_r_code`: Generate R analysis code
- `generate_stata_code`: Generate Stata analysis code
- `generate_python_code`: Generate Python analysis code
- `code_template`: Get code template for method
- `visualization_code`: Generate visualization code
- `table_code`: Generate publication-ready table code
- `debug_code`: Debug statistical code
- `optimize_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](LICENSE) for details.
## Author
Sean Shin ([@seanshin0214](https://github.com/seanshin0214))
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
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Built with [Model Context Protocol](https://modelcontextprotocol.io/) and [ChromaDB](https://www.trychroma.com/)