Carrier Accounting MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Carrier Accounting MCPingest the latest Nationwide Excel statement in trial mode"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Carrier Accounting MCP
Insurance Carrier Accounting Automation for Snellings Walters Insurance
Automates the full carrier statement lifecycle: ingest → normalize → validate → review → post to Applied Epic.
Quick Start
# 1. Clone and setup
git clone <repo>
cd carrier-accounting-mcp
pip install -r requirements.txt
playwright install chromium
# 2. Configure
cp .env.example .env
# Edit .env with your BigQuery and Epic credentials
# 3. Create BigQuery tables
bq query --use_legacy_sql=false < data_lake/schemas/staging_tables.sql
# 4. Start the MCP server (trial mode by default — safe)
python mcp_server/server.py
# 5. Start the monitoring dashboard
streamlit run dashboard/daily_monitoring.py
# 6. Run tests
pytest tests/ -vRelated MCP server: MCP-Finance-Reconciliation
Core Workflow
1. ingest_carrier_statement(file, carrier, mode="trial")
↓ Parses PDF or Excel, normalizes with Claude LLM,
validates against BigQuery, stages for review
2. Daily: accounting team reviews dashboard at localhost:8501
↓ Reviews exception queue, approves/rejects transactions
3. When ready for live: set mode="live" per carrier
↓ Auto-posts ≥95% confidence transactions to Epic
↓ <95% still go to human review queueSupported Carriers
Nationwide (Excel)
Travelers (PDF)
(Add more — see docs/adding_carriers.md)
Documentation
Doc | Contents |
| Full project context for Claude Code sessions |
| How to onboard a new carrier |
| Guide for the accounting team |
| Applied Epic SDK configuration |
| Template for new carrier configs |
Architecture
Carrier Files (PDF/Excel/Portal)
→ Ingestion (pdfplumber / pandas / playwright)
→ Normalization (Claude LLM → canonical schema)
→ Validation (BigQuery: policy match, duplicate check)
→ Confidence Scoring (auto ≥95%, review 80-94%, reject <80%)
→ Staging (BigQuery shadow table in trial / live table in live)
→ Applied Epic SDK (live mode only)
→ Audit Trail (BigQuery)
→ Daily Dashboard (Streamlit)Safety Features
Trial mode default: Zero Epic writes until explicitly switched to live
Confidence thresholds: Only ≥95% confidence transactions auto-post
Duplicate detection: Prevents double-posting
Rollback support: Can void Epic entries if needed
Full audit trail: Every transaction tracked source → Epic entry ID
Human review queue: Exceptions always go to accounting team before posting
This server cannot be deployed
Maintenance
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