This repository is a lightweight workspace for using AI as a solutions architect.
This generates cross-repository plans of action. You must define target repositories in repos.txt, configure credentials and MCP access, and use AI to produce implementation plans.
- Create architecture and implementation plans
- Analyze cross-system impact
- Keep planning context centralized (
SYSTEMS_MAP.mdandsystems_map.json)
You do not need to clone all service repositories into this folder.
Workflow:
- Fill
repos.txtwithowner/repoentries - Fill secrets and config in
.env - Fill MCP settings in
.vscode/mcp.json - Generate/update system map via
python3 generate_system_map.py - Ask AI architect for a plan
Create .env from example:
cp .env.example .envYou must replace:
WEBHOOK_URLwith your n8n RAG codesearch webhook URLGITHUB_TOKENwith a real token that can access your target repos
Note: generate_system_map.py requires GITHUB_TOKEN.
repos.txt must contain one repository per line in owner/repo format.
Example:
bitovi-training/api-tests
bitovi-training/loyalty-service
bitovi-training/order-serviceYou must replace:
GITHUB_PATin the Authorization header with your real GitHub PAT (or your MCP client's env substitution syntax)
You should also verify:
enterpriseCodepath (../enterprise-ai-mcp/src/index.ts) is correct in your local workspace
Run:
python3 generate_system_map.pyThis reads repos.txt and writes systems_map.json with repo metadata and inferred architecture signals.
AGENTS.md- AI solutions architect operating guideSYSTEMS_MAP.md- AI-generated system map in contextsystems_map.json- generated machine-readable system mapgenerate_system_map.py- map generator scriptrepos.txt- repositories to analyze.env.example- env template.vscode/mcp.json- MCP server config
GITHUB_TOKEN is required- Add
GITHUB_TOKEN=...to.env
- Add
- GitHub MCP auth fails
- Check bearer token value in
.vscode/mcp.json
- Check bearer token value in
- Wrong repos in generated map
- Fix
repos.txtand rerunpython3 generate_system_map.py
- Fix