openpharma-org/medicaid-mcp-server

Unofficial Medicaid MCP Server

Model Context Protocol (MCP) server for Medicaid public data access via data.medicaid.gov and state formularies

Features

State Formulary Coverage

Access Medicaid formularies for 5 states covering 43% of US Medicaid beneficiaries (32M of 74M):

• California - 40K drugs with NDC codes, prior authorization requirements, tier-based pricing
• New York - 37K drugs with MRA pricing, daily updates, preferred drug lists
• Ohio - 76K drugs with comprehensive step therapy and quantity limit data
• Texas - 4.7K drugs with multi-program pricing (Medicaid, CHIP, specialty programs)
• Illinois - 5.7K drugs with intelligent cross-state NDC enrichment (61.7% coverage)

Pricing & Utilization Data

• NADAC Drug Pricing - National average drug acquisition costs (1.5M NDCs, weekly updates)
• Federal Upper Limits - Generic drug maximum reimbursement (2.1M records, monthly updates)
• Drug Rebate Program - Manufacturer product information and rebate agreements (~3M records)
• State Drug Utilization - Prescription volume by state, drug, and quarter (5.3M records)
• Enrollment Trends - Monthly Medicaid/CHIP enrollment by state (all 50 states + territories)

Technical Features

• Hybrid Architecture - Optimized data access: in-memory caching for small datasets, streaming API for large datasets
• Automatic Pricing Integration - Formulary queries auto-enrich with NADAC pricing data
• Intelligent Enrichment - Illinois formulary enhanced via cross-state NDC matching (CA/NY/OH sources)

Usage

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "medicaid": {
      "command": "node",
      "args": ["/path/to/medicaid-mcp-server/build/index.js"]
    }
  }
}

API Reference

Unified Tool: medicaid_info

The server provides a single tool with multiple methods:

State Formulary Search

{
  "method": "search_state_formulary",
  "state": "CA",  // CA, NY, OH, TX, IL
  "label_name": "OZEMPIC",
  "limit": 10
}

Parameters:

• state (required): State code (CA, NY, OH, TX, IL)
• label_name: Brand/trade name
• generic_name: Generic drug name
• ndc: 11-digit NDC code
• requires_pa: Prior authorization filter (true/false)
• has_ndc: Filter for drugs with NDC codes (Illinois only)
• limit: Max results (default: 10)

State-Specific Parameters:

California:

• tier: Cost ceiling tier ("Brand" or "Generic")
• extended_duration: Extended duration eligibility (true/false)

Texas:

• pdl_pa: PDL prior authorization (true/false)
• clinical_pa: Clinical prior authorization (true/false)
• program: Program filter (medicaid, chip, cshcn, etc.)
• max_price / min_price: Price range filters

New York:

• preferred: Preferred drug status (true/false)
• is_brand: Brand vs generic filter (true/false)
• max_price / min_price: MRA cost range

Drug Pricing

{
  "method": "get_nadac_pricing",
  "drug_name": "ibuprofen",
  "limit": 10
}

Parameters:

• drug_name: Drug name (fuzzy match)
• ndc: Specific 11-digit NDC code
• limit: Max results (default: 10)

Enrollment Trends

{
  "method": "get_enrollment_trends",
  "state": "CA",
  "start_date": "2023-01-01",
  "end_date": "2024-12-31"
}

Federal Upper Limits

{
  "method": "get_federal_upper_limits",
  "ingredient": "NYSTATIN",
  "limit": 10
}

Drug Rebate Information

{
  "method": "get_drug_rebate_info",
  "drug_name": "ozempic",  // or labeler_name: "novo nordisk"
  "limit": 10
}

State Drug Utilization

{
  "method": "get_drug_utilization",
  "state": "CA",
  "drug_name": "OZEMPIC",
  "year": 2024,
  "quarter": 4,
  "limit": 10
}

Architecture

The server uses a hybrid data access strategy optimized for performance and memory efficiency:

Cached Datasets - Small, frequently accessed data loaded into memory:

• State formularies (CA, NY, OH, TX, IL) - Excel/CSV/JSON/Text parsing with TTL-based refresh
• NADAC pricing (123 MB) - Weekly CSV download, cached for fast lookups
• State enrollment (3.6 MB) - Monthly snapshots, cached for trend analysis

Streaming API - Large datasets queried on-demand via CMS DKAN API:

• Federal Upper Limits (196 MB, 2.1M records)
• Drug Rebate Program (291 MB, ~3M records)
• State Drug Utilization (192 MB, 5.3M records)

Memory Footprint: ~215 MB total for cached datasets, minimal for API queries

Performance Characteristics

Data Sources

Query Examples

State Formulary Search with Automatic Pricing

// Find GLP-1 drugs in California
{
  "method": "search_state_formulary",
  "state": "CA",
  "generic_name": "semaglutide",
  "limit": 10
}
// Returns formulary data with automatic NADAC pricing integration

Multi-State Enrollment Comparison

{
  "method": "compare_state_enrollment",
  "states": ["CA", "TX", "NY", "FL"],
  "month": "2024-09"
}

Cross-State NDC Enrichment

// Illinois formulary with intelligent enrichment
{
  "method": "search_state_formulary",
  "state": "IL",
  "label_name": "OZEMPIC",
  "limit": 10
}
// Returns IL formulary enriched with NDC codes from CA/NY/OH (61.7% coverage)

Use Cases

Market Access & Strategy

• State formulary coverage analysis and prioritization
• Prior authorization landscape mapping
• Competitive tier placement assessment

Pricing Intelligence

• NADAC price trend analysis and forecasting
• Multi-state pricing comparisons
• Rebate program eligibility verification

Policy & Economics

• Medicaid expansion impact analysis
• State enrollment forecasting and growth trends
• Utilization pattern analysis by geography

Limitations

• Provider-level utilization data not available (use Medicare MCP for provider analytics)
• Individual beneficiary claims require CMS Data Use Agreement (T-MSIS/TAF)
• No HCPCS procedure-level analysis (state-level aggregate data only)