Uploaded 'claude.md'

docs: add CLAUDE.md for AI assistant onboarding

Adds a CLAUDE.md at the repo root documenting project purpose, directory
layout, setup, run/test commands, the shard registration pattern,
canonical schema conventions, SOC 2 audit middleware behavior, shard
status, and branching guidelines.
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# nexus-mcp
Self-hosted MCP server that bridges enterprise systems (Active Directory, Entra ID, Workday, BMC Helix ITSM, Lansweeper, Intune, FedEx) with LLM-based agents via the Model Context Protocol. Normalizes data into canonical schemas, detects cross-system inconsistencies, and logs every tool call for SOC 2 compliance.
## Repository Layout
```
nexus-mcp/ # Main Python package
src/
main.py # Orchestrator: loads enabled shards, applies audit middleware
shards/ # One module per integration domain
identity.py # AD + Entra ID (15 tools) — live
workday.py # Workday HCM (12 tools) — integration in progress
audit.py # Cross-system drift scanning (6 tools) — live
itsm.py # BMC Helix ITSM — stub
assets.py # Lansweeper + Intune — stub
logistics.py # FedEx — stub
lib/
config.py # Pydantic BaseSettings for all system credentials
schemas.py # Canonical data models (CanonicalUser, Device, Incident, …)
adapters.py # System API response → canonical schema transforms
ad_adapter.py # Production LDAP/Active Directory backend
audit_log.py # SOC 2 JSONL logger (append-only, auto-redacts secrets)
drift_detection.py # Cross-system mismatch scanning logic
mock_data.py # Synthetic test data with pre-seeded drift scenarios
resilience.py # Retry/timeout/circuit-breaker patterns
*_client.py # REST/GraphQL clients (Entra, Workday, Helix, Lansweeper, Intune, FedEx)
tests/
identity_tests/ # AD/Entra unit + integration tests
workday_tests/ # Workday drift detection tests
test_resilience.py
.env.example # All config keys with comments
pyproject.toml # Package config, entry point, test markers
list_tools.py # Browse all registered MCP tools
verify_mcp_protocol.py # Validate MCP compatibility
documentation/
scripts/
.github/
agents/ # AI assistant instructions (Frank v6, Data Analyst, …)
prompts/ # 30+ workflow automation prompts
```
## Setup
```bash
cd nexus-mcp
python -m venv .venv
source .venv/bin/activate # Windows: .\.venv\Scripts\Activate.ps1
pip install -e .
cp .env.example .env
```
Edit `.env` before starting. The key flags:
| Variable | Purpose |
|---|---|
| `USE_MOCK=true` | Run all tools on synthetic data — no credentials needed |
| `ENABLE_IDENTITY=true` | Load the identity shard (AD + Entra) |
| `ENABLE_WORKDAY=true` | Load the Workday shard |
| `ENABLE_AUDIT=true` | Load the audit/drift shard |
| `ENABLE_ITSM/ASSETS/LOGISTICS` | Load stub shards |
| `AUDIT_LOGGING_ENABLED=true` | Write SOC 2 audit log to `logs/nexus_audit.jsonl` |
For live mode, fill in the system-specific credential sections (AD, Entra, Workday, etc.) in `.env`.
## Running
```bash
# From nexus-mcp/ directory
python -m main
# or after pip install -e .
nexus-mcp
```
Communicates via stdio (MCP protocol). Connect via any MCP-compatible client (Claude Desktop, VS Code extension, etc.). See `documentation/VSCODE_INTEGRATION_GUIDE.md` for IDE setup.
## Testing
```bash
# All unit tests (integration tests skipped by default)
pytest
# Skip integration tests explicitly
pytest -m "not integration"
# With coverage
pytest --cov=src --cov=lib
# Single file
pytest tests/identity_tests/test_ad_adapter.py
# Browse all registered tools
python list_tools.py
# Verify MCP protocol compliance
python verify_mcp_protocol.py
# Watch audit log
tail -f logs/nexus_audit.jsonl
```
Mock mode (`USE_MOCK=true`) is the fastest way to exercise all tools — no external systems required. `lib/mock_data.py` has pre-seeded drift scenarios for realistic testing.
## Architecture
### Shard Pattern
Every shard exports a single `register(mcp: FastMCP) -> None` function. `main.py` reads feature flags and calls `register()` for each enabled shard. No other file changes when adding or removing a shard.
```python
# Minimal shard skeleton
def register(mcp: FastMCP) -> None:
@mcp.tool()
async def my_tool(arg: str) -> dict:
"""Tool description visible to the LLM."""
...
```
### Canonical Schemas
All system adapters transform native API responses into Pydantic models defined in `lib/schemas.py`:
- `CanonicalUser` — normalized across AD, Entra ID, Workday
- `CanonicalDevice` — normalized across Intune, Lansweeper, Helix
- `CanonicalIncident`, `CanonicalShipment`, `FieldDrift` — other domains
Use canonical types as return values; never pass raw dicts between layers.
### SOC 2 Audit Middleware
Applied in `main.py` after all shards load — wraps every tool automatically. Each call records `event_id`, `timestamp`, `tool`, `shard`, `action_category`, `args_summary` (secrets redacted), `mock_mode`, `status`, and `latency_ms` to `logs/nexus_audit.jsonl`.
## Shard Status
| Shard | Systems | Status | Notes |
|---|---|---|---|
| `identity` | AD + Entra ID | Live | 15 tools; tests passing |
| `workday` | Workday HCM | In progress | 12 tools; credentials + validation pending |
| `audit` | Cross-system drift | Live | 4 scan tools + 2 audit log query tools |
| `itsm` | BMC Helix ITSM | Stub | 6 tools planned |
| `assets` | Lansweeper + Intune | Stub | 13 tools planned |
| `logistics` | FedEx | Stub | 5 tools planned |
## Branching
- `main` — stable; changes via PR only
- `feat/`, `project/`, `chore/` — short-lived feature branches
- Rebase is intentional, not automated
- See `CONTRIBUTING.md` for full workflow