
Cernion Grid Intelligence
★ 2from energychain
87+ specialized tools for German and European energy data. Direct AI access to Marktstammdatenregister (MaStR), ENTSO-E, Redispatch 2.0, and Grid Operations for utilities and datacenters.
Cernion Energy Tools
API-first Agentic Energy Operations Layer for Stadtwerke, DSOs and energy-service teams. Cernion combines deterministic energy-domain microservices, governed agent orchestration, evidence dossiers and curated integration surfaces for Microsoft Copilot, OpenClaw and conventional REST clients.
What This Repository Is
Cernion Energy Tools is the backend runtime behind cernion.de: a Node.js/Moleculer service platform for energy-domain automation, decision support and agentic process orchestration.
It is not just a chat frontend for energy APIs. The current platform contains:
- 108 Moleculer services in
services/ - 619 OpenAPI paths in
openapi-export.json - 243 JavaScript test files under
tests/ - curated Copilot and Sidecar interfaces that expose only governed subsets of the backend
- agentic runtime components for routing, receipts, dossiers, HITL, evidence, revalidation and observability
Current package version: 0.60.8
The public website explains Cernion as an energy-intelligence and decision platform for Stadtwerke: MaStR analysis, grid planning, §14a, Redispatch, Energy Sharing, customer-service automation and Microsoft Copilot complementarity. This repository is the deeper technical system underneath that product narrative.
Why Cernion Is Agentic
Cernion is API-first, but the API is only the integration layer. The agentic part is the runtime behavior:
- Understand an energy-domain objective Examples: validate a grid-connection scenario, build a VDMI responsibility matrix, assess BESS finance risk, identify Energy Sharing data conflicts.
- Select a governed capability path
The
capability-brokermaps intent to curated service chains instead of exposing the full tool catalogue to an LLM. - Execute deterministic microservices Energy-domain calculations and regulatory checks remain code-backed and reproducible.
- Maintain process state Personal-agent sessions, receipts, dossiers, HITL items and object-store evidence allow work to continue beyond a single chat turn.
- Produce auditable artifacts Outputs are not only natural-language answers; they include dossiers, evidence packages, decision frames, validation reports, receipts and traces.
- Govern revalidation New facts can become control signals for agents: if a MaStR asset, datapoint or object-store evidence item changes, dependent decisions can be identified and rechecked.
This is the practical difference between a question-and-answer bot and an agentic energy-operations platform.
Core Architecture
External systems / humans / agents
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REST API, Copilot API, OpenClaw Sidecar, MCP-like tool surfaces
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v
Personal Agent / Capability Broker / Agent Receipts / Blueprints
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Governed Moleculer services
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Datapoints, Object Store, Knowledge RAG, Dossiers, Jobs, ObservabilityRuntime Layers
| Layer | Components | Purpose |
|---|---|---|
| Service bus | Moleculer, REST gateway, async jobs | Deterministic service execution and API exposure |
| Data layer | Object Store, Datapoints, DataSources, Knowledge RAG | Internal data, external evidence, tenant memory and source material |
| Agentic routing | Personal Agent, Capability Broker, Blueprints, Agent Receipts | Intent resolution, tool-chain selection, durable execution |
| Governance | VDMI, HITL, Clarification Policy, Interface Placeholder, Evidence Revalidation | Responsibilities, missing evidence, human decisions, gap handling |
| Integration | Full OpenAPI, Copilot subset, OpenClaw Sidecar, Webhooks, MCP-style tools | Safe use by humans, copilots, agents and automation systems |
| Observability | Metrics, traces, audit records, job status | Operation, auditability and support |
Main Domains
The platform covers several energy-industry work areas. The following list is representative; the OpenAPI export is the source of truth.
| Domain | Examples |
|---|---|
| Grid connection and fNAV | Grid-connection validation, flexible network access, connection-rejection evidence |
| VDMI governance | Verantwortlich, Durchführend, Mitwirkend, Information per process step; findings, dossiers and evidence |
| Zielnetzplanung (ZNP) | Projects, assumptions, Layer 0/1/2 assets, portfolio analysis, NOVA decisions |
| Asset and data quality | MaStR quality, asset overrides, ghost-asset alerts, datasource classification |
| Energy Sharing and settlement | §42c-style allocation, settlement checks, Redispatch ex-post reconciliation |
| EDM and market communication | MSCONS import, EDM validation, virtual meters, messkonzept checks |
| Forecasting and flexibility | Forecast engine, residual load, §14a flex events, SLP profiles |
| Finance and investment | Finance agent, fNAV economics, BESS screening, capex prioritization |
| Reporting and BI | Reporting governance, dashboard API, VNB monitoring, EWK monitoring |
| Knowledge and evidence | Knowledge RAG, evidence routing, dossiers, object-store context |
Agentic Components
Personal Agent
services/personal-agent.service.js is the user-facing orchestration layer. It keeps
conversation state, routes intents, calls deterministic services and synthesizes results
without turning the whole backend into one prompt.
Key concepts:
- layered context management ("Zwiebelmodus")
- durable execution state and resumable sessions
- file and datapoint intake
- evidence-gap handling
- work-out-loud events
- presentation-aware final artifacts
Capability Broker
services/capability-broker.service.js and src/capability-catalog.js provide curated
capability routing. This is the control point that prevents agents from seeing or choosing
the entire backend surface directly.
Examples of curated capabilities include:
vdmi_role_boundary_governancevdmi_asset_validation_governancevdmi_grid_connection_decision_governancenetzfahrplan_fnav_assessmentznp_portfolio_assessmentsettlement_a96_reconciliationfinancier_due_diligence_assessmentreporting_governance
Agent Receipts
services/agent-receipts.service.js turns repeatable agent workflows into versioned,
testable recipes. Receipts describe matching conditions, required inputs, tool plans and
knowledge plans. They are the bridge from "the agent answered" to "the platform selected a
governed, inspectable workflow".
Dossiers and Decision Frames
Cernion uses dossiers and decision frames for auditable outputs. A result can include:
- facts used
- hypotheses
- evidence gaps
- risks
- forbidden assumptions
- VDMI responsibilities
- next actions
- human-review requirements
Agentic Governance and Revalidation
Two active architecture tracks are captured in GitHub issues:
- #275 Agent Governance Runtime: Bestandsanalyse vor Umsetzungsplan
- #276 Agentic Governance Layer: Faktenänderungen als Steuerungssignal für Agenten
The target direction is that a changed fact can become a control signal for agents:
MaStR / datapoint / object-store change
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Dependency and impact analysis
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Revalidation queue
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Agent receipt / capability flow rerun
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Audit note, updated dossier, HITL item or exception caseThis is how Cernion moves from one-time API analysis toward RPA+ for commodity energy processes: standard cases are automated, exceptions are made explicit.
Integration Surfaces
Full REST API
The complete REST API is generated from Moleculer service metadata.
- Swagger UI:
GET /api/docs - OpenAPI JSON:
GET /api/openapi.json - Static export:
openapi-export.json
Regenerate and audit:
npm run export:openapi
npm run audit:openapiMicrosoft Copilot Bridge
Cernion does not expose all 600+ API paths to Microsoft Copilot. The Copilot bridge uses a
curated allowlist maintained in config/copilot-operations.json.
Relevant files:
- docs/copilot-process-bridge.md
- docs/copilot-agent.json
- docs/copilot-plugin.json
openapi-copilot.json
Generate the Copilot subset:
npm run export:openapi:copilotThe Copilot-facing surface distinguishes:
readoperations with no side effectsdraftoperations that prepare suggestionsprepareoperations requiring confirmation- consequential operations that remain blocked until explicitly governed
OpenClaw Sidecar
Cernion Energy Tools can be used from OpenClaw through the public ClawHub package @cernion/openclaw-energy-tools-sidecar. Install it in OpenClaw with:
openclaw plugins install clawhub:@cernion/openclaw-energy-tools-sidecarThe companion repository SmartEnergySolutions/cernion-openclaw-sidecar provides an OpenClaw plugin for generic Energy Sidecar providers, with Cernion as the first provider.
The product boundary is intentionally split: OpenClaw is the agent runtime for conversation, tool orchestration, memory and answer synthesis. Cernion Energy Tools is the energy-domain evidence, policy, Knowledge RAG and read-only API layer behind answers about MaStR assets, grid context, Redispatch, Zielnetzplanung, 14a/14d EnWG duties, process intake and operational status.
The sidecar consumes the Cernion Sidecar contract:
GET /api/agent-sidecar/descriptorGET /api/agent-sidecar/mcp/toolsPOST /api/agent-sidecar/mcp/tools/:name/callPOST /api/knowledge-rag/queryPOST /api/evidence-router/routePOST /api/copilot-process/intentsGET /api/_agent/capabilities[?domain=]GET /api/_agent/operations[?domain=]
The boundary is deliberately strict:
- read-only Cernion evidence lookup uses a read-only token
- process intake uses a separate process token and creates only
pending_confirmationreceipts - admin, token, HITL-resolve and production mutation paths are blocked
- domain routing remains inside Cernion, not inside the sidecar
MCP-Style Tooling
Cernion also publishes AI-agent-friendly tool descriptions through llm.txt, capability
resolution endpoints and MCP/OpenClaw-style tool lists. The public documentation page
describes this as a set of ready-to-use energy tools for Stadtwerke.
Development
npm test
npm run test:unit:ci
npm run test:tdd-matrix
npm run test:rest-usecases
npm run lint
npm run audit:openapi
npm run check:llm
npm run release:checkUseful generation commands:
npm run export:openapi
npm run export:openapi:copilot
npm run generate:llm
npm run blueprint:exportCreate a new Moleculer service:
npm run createDemonstrating Cernion
Good demos should show an agentic run, not only a chat answer.
Strong demo patterns:
- VDMI: generate a responsibility matrix per process step and detect role-boundary violations
- BESS: assess a site across grid connection, risks, revenue assumptions and financier evidence
- Energy Sharing: identify MaLo/MeLo, EDM and settlement conflicts that block the process
- MaStR/Revalidation: show how an external asset update can trigger rechecking of dependent decisions
- Copilot/Sidecar: show Cernion as the governed energy-domain backend behind a general-purpose agent
A useful agentic trace should make these visible:
User objective
-> intent and capability
-> selected receipt / blueprint
-> service chain
-> evidence used
-> gaps and risks
-> HITL / policy decision
-> dossier or decision artifact
-> audit traceDocumentation Map
| Document | Topic |
|---|---|
| docs/copilot-process-bridge.md | Curated Microsoft Copilot API subset |
| docs/v0.52-implementation-plans/personal-agent-v052-architecture-tdd.md | Personal Agent architecture and TDD contract |
| docs/v0.52-implementation-plans/v0.52.1-capability-broker.md | Capability Broker implementation plan |
| docs/observability/grafana/README.md | Grafana dashboards |
| docs/DSFA_TEMPLATE.md | Data protection impact-assessment template |
| docs/BACKEND_CONTEXT.md | Backend context for UI/frontend work |
| CHANGELOG.md | Release history |
| MCP_TOOLS.md | MCP/tool reference |
| llm.txt | Machine-readable service and capability context |
| SECURITY.md | Security policy |
git clone https://github.com/energychain/cernion-energy-tools.git
cd cernion-energy-tools
npm install
cp .env.example .env
npm startBefore it works, you'll need: CERNION_TOKENLLM_API_KEYGEMINI_API_KEY
Quickstart
Prerequisite: Node.js 22+
git clone https://github.com/energychain/cernion-energy-tools.git
cd cernion-energy-tools
npm install
cp .env.example .env
npm startDefault local endpoints:
- API:
http://localhost:3000/api - Swagger UI:
http://localhost:3000/api/docs - Web app:
http://localhost:3000/app
Full setup guide: QUICKSTART.md
Configuration
Start with .env.example. Common variables:
| Variable | Purpose |
|---|---|
CERNION_TOKEN | API token for authenticated access |
LLM_PROVIDER | LLM provider (gemini, openai-compat, ollama) |
LLM_MODEL | Model name for the selected provider |
LLM_API_KEY / GEMINI_API_KEY | Provider credentials when needed |
API_URL | Base URL used in generated OpenAPI servers and CLI share links |
PORT | API gateway port, default 3000 |
TRACING_ENABLED | Enable OpenTelemetry tracing |
OTEL_EXPORTER_OTLP_ENDPOINT | OTLP HTTP trace destination |
METRICS_PUBLIC | Expose /metrics without a full-access token |
LLM health:
GET /api/system/llm/healthObservability:
GET /metricsreturns Prometheus-compatible metrics- Grafana examples: docs/observability/grafana/README.md
Auth guide: BEARER_TOKEN_AUTHENTICATION.md
No common issues documented yet. If you hit a problem, the repository's GitHub Issues page is the best place to look.
Licensed under GPL-3.0— you can use, modify, and redistribute it under that license's terms.
License and Operator Context
License: GPL-3.0. See LICENSE.
Cernion is developed by STROMDAO GmbH in the context of the Cernion energy-intelligence platform.
Support and product feedback:
- GitHub Issues
dev@stromdao.com