quantmaster-mcp-server by seanshin0214 - MCP Server

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 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 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