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flux7-console — AI Agent Governance Platform

The problem

You deployed agents. flux7-mesh governs them. flux7-memory stores their decisions. Now you need answers :

  • Which agents are running ? What are they doing ? You have JSONL traces and terminal logs across machines. No single view.
  • Who approved what, when, and why ? Decisions are in flux7-memory, but querying them requires knowing the key format and tag conventions.
  • Is this new agent safe to promote to production ? There's no scoring, no lifecycle, no diff showing what changed since the last review.
  • Three agents are waiting for approval at 2am. Nobody is watching the terminal. The requests time out.

These are management plane problems. flux7-mesh is the data plane (runtime enforcement), flux7-memory is the memory substrate. flux7-console is the visibility and control layer that makes them manageable at scale.

What flux7-console is

A web-based governance platform for AI agents. Dashboard, approval UI, audit trail, governance engine.

flux7-console (management plane — L2 visibility + human control)
├── Trace Viewer      — reads flux7-mesh traces, aggregates stats
├── Session Browser   — session list and drill-down
├── Memory Viewer     — reads flux7-memory, displays decisions + facts
├── Approval UI       — shows pending approvals, human clicks approve/reject
├── OTEL Waterfall    — visual trace timeline from OTEL export
└── (planned) Governance Engine, Agent Catalog, Dependency Graph

Stack : Next.js 16 + TanStack Query. Backend API and PostgreSQL are scaffolded for future phases. Currently a direct HTTP client of flux7-mesh and flux7-memory.

How it fits

                    flux7-console (visibility + control)
                    ┌────────────────────────────┐
                    │  dashboard, approval UI,   │
                    │  governance, audit trail    │
                    └──────┬──────────┬──────────┘
                           │          │
              reads via    │          │  reads via
              HTTP API     │          │  Python SDK
                           │          │
                           ▼          ▼
┌─────────────────┐    ┌─────────────────┐
│   flux7-mesh    │───►│     flux7-memory        │
│   (runtime)     │    │   (memory)      │
│                 │    │                 │
│ • policy        │    │ • facts         │
│ • approvals     │    │ • decisions     │
│ • traces        │    │ • observations  │
└─────────────────┘    └─────────────────┘

flux7-console is a thin client of flux7-mesh and flux7-memory. If flux7-console goes down, everything keeps working — agents are still governed, decisions are still stored. flux7-console adds visibility, not runtime dependency.

Supervisor evaluation (L1) lives in flux7-supervisor (sup7) — a standalone agent that polls flux7-mesh approvals and resolves them via rules + LLM. flux7-console is the human layer (L2), not the judgment layer.

Agent-agnostic. flux7-console doesn't know or care which SDK produced the tool call. Claude Code, Managed Agents, LangChain, cron scripts — if it goes through flux7-mesh, flux7-console sees it.

What it enables

For the solo dev : trace viewer shows what your agents did today. Memory viewer shows what decisions were made. You don't need flux7-console on day 1 — flux7-mesh + flux7-memory are enough. Add flux7-console when you want a dashboard instead of curl.

For the team : approval UI lets any team member resolve pending approvals from a browser. Governance scoring flags risky agents before they hit production. Audit trail answers "who approved that email send at 3am."

For compliance : every decision is a fact in flux7-memory. Every tool call is a trace. flux7-console joins them : "this agent called this tool, it was auto-approved because of these 3 past decisions, here's the full chain." Query, don't grep.

What makes it different

Anthropic Console LangSmith / LangFuse flux7-console
Scope Anthropic agents only LangChain ecosystem Any agent through flux7-mesh
Governance Permission policies (allow/ask) None Rules, scoring, lifecycle, diffs
Approvals Inline in SDK None Web UI + API, team-accessible
Memory None Trace replay flux7-memory integration (decisions as facts)
Policy enforcement Basic None Full (flux7-mesh data plane)

Anthropic Console is great for Managed Agents visibility. flux7-console complements it with governance and cross-agent visibility for heterogeneous deployments.

Current state (May 2026)

  • Dashboard — Next.js 16 with mesh-oriented routes :
    • /mesh — health, connected MCP servers, tool inventory
    • /mesh/traces — trace browser
    • /mesh/sessions — session list and drill-down
    • /mesh/approvals — pending approvals, approve/deny
    • /mesh/otel — OTEL waterfall view
    • /mesh/memory — flux7-memory browser (search, filter by agent)
  • Supervisor — migrated to flux7-supervisor (sup7) as a standalone L1 agent (rules + pluggable LLM: Ollama, Anthropic, Claude Code MCP callback)
  • Next — governance engine (scoring, lifecycle), flux7-memory SDK integration, dependency graph

Progressive adoption

Day 1:   flux7-mesh only — policies + tracing (CLI, zero UI)
Day 30:  + flux7-memory — persistent memory, decision history, auto-approve
Day 60:  + flux7-console — dashboard, team approval UI, governance scoring

Each step is independently valuable. flux7-console is the last layer, not the first.

github.com/KTCrisis/flux7-console