battery-erp
This server exposes inventory-management tools for battery ERP, letting you look up parts, check stock status, list SKUs, and run human bin-count confirmation workflows.
lookup_inventory — Get available quantity and stock status for a part number/SKU.
get_inventory_status — Check inventory status and see reorder suggestions when stock is below the reorder point.
get_inventory_record — Fetch the full inventory record for a SKU, including on-hand, reserved, reorder level, and cost.
list_inventory — List status for all seeded inventory SKUs in the demo store.
create_bin_check_request — Create a human bin-count verification task for SMS/warehouse workflows, with optional notes.
record_bin_confirmation — Record a human-confirmed on-hand quantity, requiring an auth token matching BATTERY_ERP_CONFIRM_TOKEN; supports actor, notes, and request ID.
Battery ERP — Material, cell, pack, and supply-chain management with real-time
commodity pricing and Fabric Lakehouse analytics.
Covers the full battery value chain: lithium, cobalt, nickel, manganese, graphite
through cell chemistries (NMC-811, NCA, LFP, LMO) to battery packs with BOM costing,
supplier scoring, inventory management, and what-if cost scenarios.
mcp-name: io.github.icohangar-ops/battery-erp
What this is
Battery ERP manages the complete battery value chain — from raw material sourcing through cell manufacturing to pack assembly. Every cost is traceable to a specific material, supplier, and price point.
Layer | Role |
Data Models | RawMaterial, CellChemistry, BatteryCell, BatteryPack, BOMItem, Supplier, InventoryRecord, PurchaseOrder, ManufacturingBatch |
Business Rules | BOM cost rollups, inventory status management, supplier scoring (composite A-D grade), manufacturing yield tracking, price trend analysis, what-if cost scenarios |
Pricing Engine | Default material price table (20+ materials), AlphaVantage integration for live commodity prices, FRED macro overlay |
Analytics | Inventory health reports, supply chain reports, manufacturing yield reports, chemistry cost comparison dashboards |
Fabric Lakehouse | 11 Delta tables for persistent storage and SQL analytics |
Related MCP server: foundry net-industrial
Quick start
# From PyPI — https://pypi.org/project/battery-erp/
python3 -m pip install 'battery-erp[mcp]' # MCP tools
python3 -m pip install 'battery-erp[api]' # REST adapter
# From source
git clone https://github.com/icohangar-ops/battery-erp.git
cd battery-erp
python3 -m pip install -e '.[dev]'
PYTHONPATH=src python3 -m pytest tests/ -v
# Domain modules
python3 -c "
from battery_erp.pricing import calculate_cell_cost_summary, get_material_price_table
prices = get_material_price_table()
for chem in ['NMC-811', 'NMC-622', 'NCA', 'LFP', 'LMO']:
r = calculate_cell_cost_summary(chem, 50.0, prices)
print(f'{chem}: \${r[\"cost_per_kwh\"]:.1f}/kWh (BOM: \${r[\"bom_cost_usd\"]:.2f})')
"Architecture
┌──────────────────────────────────────┐
│ Raw Materials (20+ tracked) │
│ Lithium · Cobalt · Nickel · Mn · Gr │
└──────────────┬───────────────────────┘
│ BOM
┌──────────────▼───────────────────────┐
│ Cell Chemistries │
│ NMC-811 · NMC-622 · NCA · LFP · LMO │
└──────────────┬───────────────────────┘
│ cells + components
┌──────────────▼───────────────────────┐
│ Battery Packs │
│ EV · ESS · Consumer · Industrial │
└──────────────────────────────────────┘
Side modules:
┌─────────────────┐ ┌──────────────────┐ ┌──────────────────┐
│ Supplier Scoring │ │ Inventory Mgmt │ │ Cost Scenarios │
│ Composite 0-100 │ │ Reorder logic │ │ What-if analysis │
│ A/B/C/D grades │ │ Status tracking │ │ Price shock model │
└─────────────────┘ └──────────────────┘ └──────────────────┘Core modules
battery_erp.core.models
All domain dataclasses:
RawMaterial— material catalog with pricing, HS codes, hazardsCellChemistry— NMC-111/622/811, NCA, LFP, LMO with energy density and cycle lifeBatteryCell— cell specs (capacity, voltage, form factor, weight)BatteryPack— pack assembly (cells + BMS + thermal)BOMItem— bill of materials line item with waste factorSupplier— supplier catalog with quality rating, lead time, certificationsInventoryRecord— warehouse positions with reorder logicPurchaseOrder— PO lifecycle trackingManufacturingBatch— production batch yield trackingPriceHistory— commodity price time series
battery_erp.core.rules
Deterministic business rules:
rollup_bom_cost()— total BOM cost with material breakdown and waste costcalculate_cell_bom()— generate representative BOM for any chemistrycalculate_pack_bom()— pack-level BOM (cells + casing + BMS + cooling)update_inventory_status()— recalculate in_stock/low/out_of_stockcheck_reorder_suggestions()— generate PO suggestionscalculate_batch_metrics()— aggregate manufacturing yieldanalyze_price_history()— price trend analysis with volatilityestimate_cell_cost_impact()— what-if cost scenario modelingcalculate_pack_metrics()— pack energy density and efficiency
battery_erp.supply_chain
Supply chain management:
score_supplier()— composite score (quality 35%, OTD 35%, lead time 20%, certs 10%)rank_suppliers()— rank by score, filter by materialcreate_purchase_order()— PO creation from supplier dataanalyze_po_pipeline()— PO pipeline analysis (overdue detection, lead time tracking)suggest_dual_sourcing()— dual-sourcing strategy recommendation
battery_erp.pricing
Commodity pricing:
get_material_price_table()— default prices for 20+ battery materialscalculate_cell_cost_summary()— quick cost estimate per chemistryupdate_prices_from_alpha_vantage()— live commodity price fetchupdate_prices_from_fred()— macro economic indicators
battery_erp.analytics
Reporting:
generate_inventory_report()— full inventory health dashboardgenerate_supply_chain_report()— supplier + PO pipeline reportgenerate_manufacturing_report()— yield metricsgenerate_pricing_report()— chemistry cost comparison + price trends
Chemistry cost comparison (default prices, 50Ah cell)
Chemistry | BOM Cost | $/kWh | Cathode % | Key feature |
LFP | Lowest | ~$50-55 | ~35% | No Co/Ni, ultra-safe, 4000+ cycles |
LMO | Low | ~$55-60 | ~40% | Low cost, power tools |
NMC-111 | Medium | ~$70-80 | ~50% | Balanced, legacy |
NMC-622 | Medium | ~$75-85 | ~48% | Good energy-cost balance |
NMC-811 | Higher | ~$80-90 | ~52% | High energy, EV dominant |
NCA | Highest | ~$85-95 | ~55% | Tesla flagship, 270 Wh/kg |
Microsoft Fabric Integration
Fabric Notebooks
Notebook | Purpose |
| Create all 11 Delta tables with seed data |
| Full cost analytics dashboard (chemistry comparison, pack costing, inventory, suppliers, price trends, scenarios) |
Delta Table Schema
Table | Key Columns |
| material_id, name, category, unit_price_usd, price_source, hs_code |
| chemistry_id, name, cathode_type, energy_density_wh_per_kg, cycle_life |
| cell_id, sku, chemistry, form_factor, nominal_capacity_ah, energy_wh, weight_kg |
| pack_id, sku, cell_sku, total_cells, nominal_capacity_kwh, pack_weight_kg |
| bom_id, parent_sku, material_name, quantity_per_unit, unit_cost_usd, waste_factor_pct |
| supplier_id, name, country, materials_supplied, quality_rating, lead_time_days |
| record_id, sku, material_name, quantity_on_hand, quantity_reserved, reorder_point |
| po_id, po_number, supplier_name, quantity, total_usd, status, expected_delivery |
| material_name, price_usd, as_of, source |
| batch_id, product_sku, chemistry, quantity_produced, quantity_pass, yield_pct |
| scenario_id, scenario_name, material_name, current_price_usd, scenario_price_usd, pct_change |
Fabric Quick Start
Run
fabric_setup_lakehouse.pyto create all 11 Delta tablesRun
fabric_cost_dashboard.pyfor the full analytics dashboardDashboard covers: chemistry cost comparison, pack-level costing, inventory health, supplier scorecard, price trends, manufacturing yield, cost scenarios
Inventory adapters (REST + MCP)
Battery ERP is a domain library, not a hosted ERP. For SMS / text-line and
agent workflows, a shared InventoryService sits under both a thin REST API and
an MCP server. Full detail: docs/INTEGRATION.md.
SMS / ClickSend Cursor / Claude (stdio MCP)
│ │
▼ ▼
REST API (port 8088) battery_erp.mcp
└──────────┬──────────────┘
▼
InventoryService
▼
InMemoryInventoryStore (demo)
▼
Human bin confirmationDo not call MCP from a browser. Keep REST and MCP in separate terminals.
Install (macOS / zsh)
Use python3. Quote pip extras so zsh does not glob them:
cd ~/Desktop/icohangar-repos/battery-erp
python3 -m pip install -e '.[dev]' # api + mcp + pytestTerminal A — REST (text-line backend)
cd ~/Desktop/icohangar-repos/battery-erp
export BATTERY_ERP_CONFIRM_TOKEN=dev-secret
export BATTERY_ERP_AUDIT_LOG=/tmp/battery-erp-audit.jsonl
PYTHONPATH=src python3 -m battery_erp.api
# Uvicorn → http://127.0.0.1:8088curl -s http://127.0.0.1:8088/health
curl -s http://127.0.0.1:8088/inventory/lookup/lithiumTerminal B — MCP (agents / Cursor only)
Leave Terminal A running. In a new terminal:
cd ~/Desktop/icohangar-repos/battery-erp
export BATTERY_ERP_CONFIRM_TOKEN=dev-secret
PYTHONPATH=src python3 -m battery_erp.mcpThat process stays quiet on stdio — normal for MCP hosts. Do not paste this into the API terminal.
Cursor MCP config
Add to ~/.cursor/mcp.json (absolute paths; python3 not python):
{
"mcpServers": {
"battery-erp": {
"command": "python3",
"args": ["-m", "battery_erp.mcp"],
"env": {
"PYTHONPATH": "/Users/YOU/Desktop/icohangar-repos/battery-erp/src",
"BATTERY_ERP_CONFIRM_TOKEN": "replace-me",
"BATTERY_ERP_AUDIT_LOG": "/tmp/battery-erp-audit.jsonl"
}
}
}
}Then reload MCP servers in Cursor. Tools exposed: lookup_inventory,
get_inventory_status, get_inventory_record, list_inventory,
create_bin_check_request, record_bin_confirmation.
Surface | Entry | Shared layer |
REST |
|
|
MCP | tools above (mcp SDK 2.x | same |
Mutating bin confirmation requires BATTERY_ERP_CONFIRM_TOKEN and optionally
writes JSONL audit to BATTERY_ERP_AUDIT_LOG.
Directory / registry packaging: see PUBLISH.md (glama.json,
Dockerfile, server.json).
Directory | Link |
PyPI | |
MCP Registry |
|
Glama |
Tests
PYTHONPATH=src python3 -m pytest tests/ -v
# Domain tests + inventory service / REST / MCP scaffoldUse cases
Cell manufacturers — BOM cost tracking across chemistries, yield optimization
Pack integrators — pack-level cost estimation, supplier selection
Procurement — supplier scoring, dual-sourcing, PO pipeline management
Finance — commodity price risk, what-if scenarios, inventory valuation
C-suite — dashboard showing $/kWh trends, supply chain resilience, cost reduction opportunities
License
MIT. See LICENSE.
CHP Governance
This repository is hardened with the Consensus Hardening Protocol (CHP), Cubiczan's decision-governance layer for multi-agent AI systems.
Protocol Layers
R0 Gate: All decisions must pass Solvable, Scoped, Valid, Worth_it checks
Foundation Disclosure: 1-3 weakest assumptions, 1-2 invalidation conditions, 1 key vulnerability
Adversarial Layer: Mandatory devil's advocate at Phase 0 and Round 3
State Machine: EXPLORING → PROVISIONAL → PROVISIONAL_LOCK → LOCKED
Third-Party Validation: Independent CONFIRM/REJECT before lock
Domain Configuration
Category: Mining / Supply Chain
Foundation Threshold: 75
CFO Accuracy Guard: Disabled
Compliance Artifacts
File | Purpose |
| Decision state transitions |
| Domain-calibrated thresholds |
| Standardized challenge templates |
| Compliance tracking & audit trail |
CHP Version
cognitive-mesh-orchestrator 0.1.0 | Protocol Docs
Demo
Handheld — Parts Bin Text Line
Mobile capture from the live lead page (parts-bin-text-line--icohangar.replit.app). SMS → text-line → Battery ERP inventory check → human bin confirm.
Available Tools
6 toolscreate_bin_check_requestC
Create a human bin-count verification task for SMS / warehouse workflows.
Inputs: part_number (required), notes.
get_inventory_recordB
Return the full inventory record for a SKU (on-hand, reserved, reorder, cost).
Inputs: sku (required).
get_inventory_statusC
Get inventory status plus reorder suggestion when below reorder point.
Inputs: part_number (required).
list_inventoryB
List status for all seeded inventory SKUs (demo store).
Inputs: no named parameters.
lookup_inventoryB
Look up available quantity and stock status for a part number or SKU.
Inputs: part_number (required).
record_bin_confirmationC
Record a human-confirmed on-hand quantity. Requires auth_token matching BATTERY_ERP_CONFIRM_TOKEN.
Inputs: auth_token (required), part_number (required), actual_quantity (required), actor, +2 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 6 tools
lookup_inventory, get_inventory_status, and get_inventory_record all take a SKU and return overlapping inventory quantities/status, so their boundaries are unclear. list_inventory and the two bin-check tools are distinct, but the three inventory getters could easily be misselected.
All names are snake_case and verb-led, with read operations using lookup/get/list and write operations using create/record. The pattern is mostly predictable, with only a minor inconsistency between lookup_inventory and the get_inventory_* family.
Six tools is a well-scoped set for a focused inventory ERP demo: four query variants plus two bin-count workflow actions. Each tool has a reasonable role, and the count is neither bloated nor too thin.
The set covers inventory queries and the bin-confirmation workflow, but lacks lifecycle operations such as SKU creation/update or any way to list pending bin-check requests. Reorder suggestions are generated but there is no tool to act on them, creating a dead end.
Related MCP Connectors
Supply chain operations: dock scheduling, check-in, doors, inventory, orders and freight.
Warehouse digital twin: what-if simulation and AI optimisation of slotting, batching and labour.
Real-time supply chain risk intelligence — 24 tools, proprietary indices, predictive signals
Cross-OEM industrial machine intelligence: identity, normalization, automation, attestation.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceA custom implementation for real-time supply chain optimization that enables parallel tool calling to provide intelligent inventory management recommendations and actionable insights in response to live supply chain events.6-
- FlicenseAqualityBmaintenanceCross-OEM industrial machine intelligence. Normalizes telemetry across 16 manufacturer families (Fanuc, Siemens, Haas, DMG Mori, Mazak), enables plain-English operational automation, and produces tamper-evident work records. 14 MCP tools.14-
- FlicenseNot gradedqualityBmaintenanceAn AI-powered EV Digital Twin platform for battery health monitoring, predictive maintenance, fleet analytics, and intelligent decision support using MCP tools for SOH prediction and RUL estimation.5-
- FlicenseNot gradedqualityCmaintenanceEnables supply chain management tasks such as tracking shipments, managing inventory, and supplier scorecards through MCP protocol.24 PyPI-