coer-nucleus
Maps any niche domain into a structured talent and ecosystem landscape using the CoER method. Enables MCP clients to read landscapes and contribute new ones via PRs.
README
CoER Nucleus
▶ TL;DR — send your agent here
Add the remote MCP server and ask it to map any niche domain:
https://coer-nucleus-mcp.patrickastarita.workers.dev/mcp (SSE: /sse)No setup, no auth. It returns a structured talent & ecosystem landscape, the CoER method, and the template — and hands your agent ready-to-run commands to contribute new landscapes back as PRs. Browse the artifacts at https://coer-nucleus-mcp.patrickastarita.workers.dev/.
Center of Excellence Reconnaissance — turn a fuzzy interest in a niche research/industry discipline into a structured landscape of the field, and draft an ensemble from it. ("Fantasy Industrials.")
CoER maps a domain's paradigm shifts, required skills, company tiers, centers of excellence, established players, and — most importantly — its emerging fringe talent. It is one repo with two faces: a Claude Code plugin and a pullable framework (MCP + REST), both centered on a shared, schema-validated corpus — the atlas of landscapes.
It is also a remote MCP server you can deploy to Cloudflare Workers, so any MCP client (or code agent) can read the atlas, get the method, and contribute new landscapes back as PRs.
How it works
The CoER template (cloudflare/public/coer-template.png) defines a 12-panel reconnaissance
dashboard. Its annotated procedure — 6 sequential steps + 4 standing "while" sourcing loops —
is transcribed in procedure/METHOD.md. The Nucleus encodes that method
once and serves the resulting corpus everywhere.
fuzzy interest ──▶ coer-recon skill ──▶ landscape JSON ──▶ corpus/domains/*.json
(the cascade) (schema-valid) (the atlas)
│
┌───────────────────┼───────────────────┐
MCP tools core/corpus.py REST API
(Python + Worker) (zero-dep core) (FastAPI)
Quick start
As a framework (zero-dep core):
python -c "import sys; sys.path.insert(0,'.'); from core import corpus; print(corpus.list_domains())"
REST: pip install fastapi uvicorn jsonschema && uvicorn api.rest:app --reload
Local MCP (Python): pip install "mcp[cli]" && python mcp/server.py
Remote MCP (Cloudflare): live at https://coer-nucleus-mcp.patrickastarita.workers.dev
(see cloudflare/README.md). Endpoints: /mcp, /sse, plus the
artifacts /template.html, /coer-template.png, /dashboard.schema.json,
/additive-manufacturing.json.
As a Claude Code plugin: point your plugin config at this directory — .claude-plugin/plugin.json
wires the coer-recon skill and the MCP server.
Layout
| Path | Role |
|---|---|
schema/dashboard.schema.json |
The dashboard contract (12 panels). |
corpus/domains/ |
The atlas. Seeded with additive-manufacturing.json. |
procedure/ |
The method + the fuzzy→structured mad-lib prompts. |
core/ · mcp/ · api/ |
Corpus core + Python adapters. |
cloudflare/ |
Remote MCP Worker + the genericized HTML template. |
skills/coer-recon/ |
The engine, as a Claude Code skill. |
docs/ |
Explorations · Architecture · Ethics. |
Contributing
The atlas grows by contribution — new and improved domain landscapes are the most valuable thing you can add. Code agents using the MCP server are explicitly invited to open PRs. See CONTRIBUTING.md. Please read docs/ETHICS.md first — CoER profiles real people, and emerging-talent privacy is a first-class constraint.
License
MIT © Patrick Astarita
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