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MCP server for WRDS financial data access — credit analysis tools

Project description

wrds-mcp

An MCP server that gives AI assistants (Claude Code, Claude Desktop, etc.) natural language access to WRDS financial data for credit and equity analysis.

29 tools across bonds, credit ratings, financials, equity, loans, screening, and comps — plus a guarded SQL escape hatch and schema discovery for ad-hoc analysis.

Requires a WRDS account. This tool is a client for WRDS (Wharton Research Data Services). You must have your own WRDS subscription (academic or institutional) to use it. This project is not affiliated with, endorsed by, or sponsored by WRDS or the Wharton School.

Prerequisites

  • Python 3.10+
  • A WRDS account with access to the datasets you want to query (CRSP, Compustat, TRACE, FISD, DealScan, etc.)

Installation

pip install wrds-mcp

Or from GitHub:

pip install git+https://github.com/marianosalinas/wrds-mcp.git

For development:

git clone https://github.com/marianosalinas/wrds-mcp.git
cd wrds-mcp
pip install -e ".[dev]"

Configuration

1. WRDS Credentials

Create a .env file in your working directory or set environment variables:

WRDS_USERNAME=your_username
WRDS_PASSWORD=your_password

Or copy the included example:

cp .env.example .env

2. Add to Claude Code

Create a .mcp.json in your project directory:

{
  "mcpServers": {
    "wrds": {
      "command": "wrds-mcp",
      "type": "stdio"
    }
  }
}

Or add to your global Claude Code settings (~/.claude/settings.json):

{
  "mcpServers": {
    "wrds": {
      "command": "wrds-mcp"
    }
  }
}

3. Add to Claude Desktop

Add to your Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "wrds": {
      "command": "wrds-mcp"
    }
  }
}

Tools

Bonds (TRACE / FISD / bondret)

Tool Description
get_bond_price_history Daily VWAP price/yield per CUSIP — auto-routes between TRACE Enhanced and raw TRACE, with 144A fallback
get_bond_transactions Individual TRACE trades with price, yield, volume
get_bond_yield_history Yield time series for a specific CUSIP
get_company_bonds All outstanding bonds from FISD (coupon, maturity, seniority, covenants)
get_bond_returns Monthly return, yield, spread, duration from bondret
get_bond_covenants Protective covenants, call/put schedules, sinking funds

Credit Ratings (bondret + Compustat)

Tool Description
get_credit_ratings Current S&P, Moody's, and Fitch ratings
get_ratings_history Multi-agency rating changes over time

Financial Metrics (Compustat)

Tool Description
get_leverage_metrics Debt/EBITDA, net debt/EBITDA, total debt trends
get_coverage_ratios Interest coverage, fixed charge coverage
get_liquidity_metrics Current ratio, cash, short-term investments
get_quarterly_leverage Quarterly debt/TTM-EBITDA trending
get_credit_summary Combined snapshot: leverage + coverage + ratings + bonds + covenants + loans
get_company_overview Everything: stock performance + full credit profile

Equity (CRSP)

Tool Description
get_stock_price_history Daily/monthly prices with auto-frequency selection
get_stock_returns Compounded cumulative + annualized returns
get_stock_summary Latest price, 52-week range, market cap, YTD return

Syndicated Loans (DealScan)

Tool Description
get_loan_terms Facility details, pricing, maturity
get_loan_covenants Financial and net worth covenants

Screening & Relative Value (bondret)

Tool Description
screen_issuers Find issuers by rating, leverage, sector, market cap
screen_bonds Find bonds by spread, yield, coupon, maturity, rating
get_market_benchmarks Monthly index-style returns for IG/HY/rating buckets
get_relative_value Compare issuer bonds vs rating-peer averages (cheap/rich/fair)

Comps (multi-source)

Tool Description
get_comps_table Side-by-side comparison of up to 20 issuers: ratings, financials, bond stats, equity returns. Falls back to FISD for 144A issuers not in bondret.

Discovery & Ad-hoc

Tool Description
get_data_catalog Live catalog of all datasets with date coverage and tool routing
get_table_schema Column metadata with types and human-readable descriptions
resolve_identifier Resolve ticker to gvkey, permno, or FISD issuer_id
query_wrds Guarded read-only SQL for anything not covered by curated tools (schema-allowlisted, 10K row limit, 30s timeout)

Example Prompts

Once configured, just ask Claude naturally:

  • "What's Ford's credit profile? Include ratings, leverage, and bond spreads."
  • "Compare F, GM, and STLA — build me a comps table."
  • "Screen for BB-rated issuers with leverage under 4x and market cap over $5B."
  • "Show me the HY market benchmark returns for the last 12 months."
  • "Is Ford's 2030 bond cheap or rich relative to BBB peers?"
  • "What are the covenant terms on Delta's syndicated loans?"
  • "Pull TRACE transactions for Apple bonds in Q4 2024."

Data Sources

Source Tables Coverage
CRSP dsf_v2, msf_v2 Daily/monthly stock data
TRACE trace, trace_enhanced_clean, trace_btds144a Bond transactions (raw, cleaned, 144A)
bondret wrdsapps_bondret.bondret Monthly bond returns, ratings, spreads
FISD fisd_mergedissue, fisd_mergedissuer, covenants/call/put/sink Bond characteristics
Compustat funda, fundq, security, adsprate Financials, ticker resolution, ratings
DealScan facility, package, borrower, company, currfacpricing, covenants Syndicated loans

Architecture

src/wrds_mcp/
├── server.py             # FastMCP entry point, mounts 9 sub-servers
├── db/connection.py      # Singleton WRDS connection with retry
└── tools/
    ├── catalog.py        # Tier 3: discovery (3 tools)
    ├── query.py          # Tier 2: guarded SQL (1 tool)
    ├── equity.py         # Tier 1: CRSP stocks (3 tools)
    ├── bonds.py          # Tier 1: TRACE/FISD/bondret (6 tools)
    ├── ratings.py        # Tier 1: credit ratings (2 tools)
    ├── financials.py     # Tier 1: Compustat fundamentals (6 tools)
    ├── loans.py          # Tier 1: DealScan loans (2 tools)
    ├── screening.py      # Tier 1: screening & relative value (4 tools)
    └── comps.py          # Tier 1: comps table (1 tool)

Three tiers:

  1. Curated tools (25) — domain logic, auto-routing, multi-source resolution
  2. Guarded SQL (1) — escape hatch for ad-hoc queries with safety validation
  3. Discovery (3) — catalog, schema introspection, identifier resolution

Testing

pytest

307 tests, 90% coverage. All tests mock the WRDS connection — no credentials needed to run them.

Disclaimer

This project is an independent, open-source tool. It is not affiliated with, endorsed by, or sponsored by WRDS, the Wharton School, or the University of Pennsylvania.

  • You are responsible for complying with your WRDS subscription terms and any data redistribution restrictions.
  • This tool provides read-only access to data you are already licensed to use — it does not bypass any access controls.
  • Nothing in this tool constitutes financial advice. Data is provided as-is for research and analysis purposes.

License

MIT

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