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Dr. QuantMaster MCP Server

by seanshin0214
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TypeScript
Local
MIT License
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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 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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