Agentic-Nets

Governed multi-agent runtime for stateful, permission-scoped, replayable AI agents.

The no-code backend for building agent harnesses. Everything a harness needs — tools, control flow, memory, execution, agents, and guardrails — you assemble by prompting and chatting, not by writing code. Build one guarded agent or a whole virtual product team the same way, and drive it all remotely — even from your phone — through the Claude Code integration. You never open an editor; you describe what you want and the runtime builds it.

Agentic-Nets is a runtime where agents live inside formal Petri nets and use those nets as context. A net defines what an agent can see, what it can do, where outputs go, and how it communicates with other nets. One net can model a single guarded agent or several agents working together inside the same net. Multiple nets can model a development pipeline, a virtual agile team, or an entire product operating system. The same approach is not tied to software alone: you can model any domain, process, or industry with nets as long as structure, communication, coordination, and verification matter.

At a glance

Question	Answer
What is it?	A Petri-net runtime for agents, tools, memory, remote execution, and audit trails.
Why does it exist?	To make agent systems inspectable, permission-scoped, replayable, and reusable instead of hidden inside chat state.
What is public in this repo?	Licensed public source for the gateway, executor, vault, CLI, chat bot, MCP server, blobstore, tool containers, deployment, and monitoring.
What is closed source?	The node, master, and Studio GUI runtime images used by the full stack. They ship from Docker Hub under the Proprietary EULA.
Current status	Beta. Suitable for evaluation, local experiments, early adopters, and contributors who are comfortable with a fast-moving stack.

Watch the product preview on YouTube: agentic-nets preview

If prompt-based agents feel powerful but structurally weak, this is the missing layer:

• Agents live in nets. Context is structured state, not a fragile chat session.
• Nets talk to nets. Teams, tools, approvals, memory, and pipelines become explicit handoffs.
• Everything stays inspectable. Tokens, tool calls, events, and emissions remain queryable and replayable.
• The same model scales up. Build one guarded developer agent or a whole product runtime with the same primitives.

Start here

Goal	Link
Start locally without reading everything	Quick local run
Try the local stack	Install in 5 minutes
See live systems already running on Agentic-Nets	See it running in production
Watch the live safe-teams net	Public read-only live demo
Understand the core model	What makes this different and ARCHITECTURE.md
Read the whitepaper — the harness control system, complete domain automation	docs/whitepaper/the-harness-control-system.html (view rendered)
Drive a stack from Claude Code	Drive it from Claude Code
Connect any MCP client (working memory + net workbench)	Connect over MCP
Contribute to the public repo	CONTRIBUTING.md and issues
Ask questions or discuss use cases	GitHub Discussions or forum.agentic-nets.com
Report a security issue	SECURITY.md

Licensing note. Agentic-Nets is a hybrid stack. Public components in this repository are licensed under BSL 1.1 and convert to Apache 2.0 on 2030-02-22. The orchestration core ships as closed-source Docker Hub images under the Proprietary EULA. See licensing before production use.

Quick local run

This starts the lightweight local stack from Docker Hub. Use the longer install section if you want monitoring, local public-service builds, Ollama cloud-model login details, or troubleshooting notes.

git clone https://github.com/alexejsailer/agentic-nets.git
cd agentic-nets/deployment

cp .env.template .env
# Edit .env and choose one provider:
# LLM_PROVIDER=claude + ANTHROPIC_API_KEY=...
# LLM_PROVIDER=openai + OPENAI_API_KEY=...
# LLM_PROVIDER=ollama for the bundled Ollama container

docker compose -f docker-compose.hub-only.no-monitoring.yml up -d

cat data/gateway/jwt/admin-secret
open http://localhost:4200

See it running in production

Not slideware — these are live systems, each one Agentic-Nets running a real harness end to end:

• forum.agentic-nets.com — a real product forum. A feature request posted here is picked up by a virtual team net, triaged, built, tested, deployed, and reported back on the thread — automatically, with every lifecycle milestone posted as it happens.
• gitanalytics.agentic-nets.com — the actual product that team is building: a live git-commit-analytics service whose new endpoints are shipped by agents, not people.
• The safe-teams net — the virtual agile team that connects the two: PM, Architect, Developer, QA, DevOps, and RTE agents coordinating through a single net — intake → design → code (a real command transition runs the coding CLI on an executor) → QA gate → deploy → status. One harness turns a forum post into a shipped, verified feature.
• agentic-nets.com — full documentation, the concept chapters, and the product tour.

Public read-only live demo

You can open the live Studio in monitor mode and watch the safe-teams net working without admin access:

1. Open agentic-nets.com/#/monitor.

2. Paste this public read-only demo token into the login form:

   07a9af1d663f899f79f08ca56050a977d41472e34cc0dd0f74abe046446f78f9
   

3. Keep Read-only access (no writes) enabled and log in.

The monitor view is scoped to the safe-teams model. It lets guests inspect the live net, token counts, event story, console, agenda, and current handoffs. Read-only sessions cannot edit nets, fire transitions, deploy changes, or use write-capable assistant personas.

You can still ask questions from the monitor. The chat is pinned to the Domain Expert (read-only) persona, which can explain what is happening in the visible system. The normal Universal Assistant, Workflow Builder, Persona, and other write-capable personas are reserved for authenticated Studio use.

What you can model with it

• Virtual developers with explicit permissions, memory, and execution boundaries.
• Virtual agile teams where planner, builder, reviewer, tester, and releaser agents coordinate through nets.
• Smart development tools that behave like reusable nets instead of throwaway prompts.
• Development pipelines that generate code, run checks, gate releases, and keep a durable audit trail.
• Product-level systems where backlog, QA, docs, incidents, and operations communicate as structured nets.
• Industry-specific operating models in software, finance, support, operations, research, healthcare, logistics, or any other domain that can be expressed as communicating nets.

Who this is for

• Builders who want agents to operate inside explicit state machines instead of loose prompt loops.
• Teams that need remote execution, approvals, secrets, and audit trails around autonomous work.
• Product engineers turning one-off agent workflows into reusable internal systems.
• Researchers and tool builders exploring Petri nets as a runtime model for agent coordination.

Probably not for you if

• You only need a one-off chat wrapper or a single scripted LLM call.
• You require every runtime component to be permissively licensed today.
• You need certified production software for regulated environments without doing your own validation.

Net of nets

One net can contain one or many agents. Many nets can also work together as a larger runtime: one can guard, one can gather, one can synthesize, one can execute, and all of them can exchange structured state through explicit flows instead of hidden prompt handoffs.

Example net

This simple crawler net shows the model in practice: places hold the state, http fetches, an agent transition categorizes content, a command transition runs remote work through an executor, and map plus pass transitions route results through the graph.

How behavior is modeled

Agentic-Nets uses seven transition types: pass, map, http, llm, agent, command, and link.

• agent transitions are the core runtime primitive. They can mimic almost any agent behavior or mode, but inside a governed net with explicit inputs, outputs, permissions, and memory boundaries.
• agent transitions can also adapt the net itself. If an agent has sufficient rights, it can read tokens in the net, create additional places and transitions, and extend the structure on demand instead of staying confined to a fixed graph.
• command transitions connect the net to remote execution. They define which executor can run a command remotely and bring the result back into the net as structured state.
• Deterministic and non-deterministic transitions coexist. Fixed logic can stay fixed, while open-ended reasoning stays open-ended, in the same runtime and on the same graph.
• This is what makes the model powerful across domains. A net can combine several cooperating agents with deterministic control flow, verification, remote execution, and cross-net communication.

Everything a harness needs — assembled by prompting

A production agent harness is all the scaffolding around the model: the tools it can call, the control flow between steps, the memory it keeps, where it runs, who is allowed to do what, and how you see what happened afterwards. Most teams hand-write that harness in code and re-write it for every new agent. Agentic-Nets gives you every one of those pieces as a first-class primitive you build by describing it — and each piece is inspectable, reusable, and governed by default.

A harness needs…	…you get it as (no code)
Tools	Reusable tool-nets (self-describing capability nets you invoke, version, and share), Docker tool containers agents start on demand, and http / command transitions
Control flow	Nets wired from seven transition types — deterministic (pass / map / http) and AI (llm / agent) lanes on the same graph, with conditional routing and capacity gates
Agents	agent transitions and ready-made assistant personas — a Universal Assistant front door, a Workflow Builder, a Persona specialist-builder, plus operator / domain-expert roles
Memory & state	Places + tokens — typed, timestamped state queryable live with ArcQL — and EMIT_MEMORY, instead of a chat session that vanishes
Execution	Distributed executors that poll egress-only (firewall-friendly, deployable anywhere) and run scoped work in Docker
Governance	rwxhludct capability roles enforced at dispatch (not in the prompt) and Vault secrets injected only at action time
Observability	Event-sourced history — replay the log, watch the live event-line, and ask what existed at any decision point
Reuse & export	Export inscriptions / PNML, publish to the tool-net library, and drop the same net into another model or deployment
Self-extension	Builder / Forge agents that create new places, transitions, and whole tool-nets inside the running system — the harness grows itself

Drive it your way — no code, any LLM

You never write code, and you are not tied to one vendor or one interface.

In the Studio (the GUI). Watch every net, token, tool call, and event as it happens, and set the whole thing up by clicking — create models, sessions, nets, places, transitions, and inscriptions, deploy them, and adapt anything live. The Studio ships several built-in assistant agents — a Universal Assistant front door, a Workflow Builder that lays down and deploys whole nets from plain language, a Persona specialist-builder, plus operator and domain-expert roles — so you get the same "just describe it" power as an external coding agent, right inside the product. The Forge meta-agent builds new reusable tool-nets on demand.

From Claude Code (remote). The agenticos-control plugin (dedicated net-designer and net-operator agents, a control skill, and slash commands) plus Claude Code's Remote Control let you drive the entire system — build nets, run pipelines, even cut a release — from anywhere, including your phone, purely by chatting. See Drive it from Claude Code.

Bring your own model. Nothing is vendor-locked. Point LLM_PROVIDER at Claude, OpenAI, or a local Ollama model (fully offline) — the same nets, personas, and tools run on whatever LLM you choose, and you can even route cheap deterministic steps to one model and deep reasoning to another.

The nine production gaps Agentic-Nets closes

1. Invisible state. Every intermediate value is a token in a typed place, queryable with ArcQL while the net runs.
2. Vanishing memory. Memory is structured state. Agents read and write lessons through places and EMIT_MEMORY.
3. Weak observability. State is event-sourced. Replay the log, inspect reductions, and ask what existed at decision time.
4. No permission model. Role tiers from r---- to rwxhl gate tools at dispatch, not in the prompt.
5. Secrets in the wrong place. Vault keeps credentials outside tokens and events, scoped per transition and injected only at action time.
6. Unsafe execution boundary. Remote executors poll over egress-only links; command work runs in scoped Docker tool containers.
7. Hard to explain why. Tool calls, results, emissions, and event trails keep provenance attached to the actual work.
8. Poor reusability. Agents are transitions with inscriptions. Export inscriptions or PNML and reuse the net elsewhere.
9. No reflexive model. Builder agents can create nets, places, arcs, transitions, and inscriptions inside the same runtime.

Why this matters for coding agents

Most coding agents disappear after they ship code. The prompt is gone, the checks are ad hoc, and the verification logic is not part of the product.

Agentic-Nets lets an agent do more than implement a feature. It can also create the surrounding operating structure: unit tests, integration tests, and even a dedicated verification net that stays in the system and can be reused against future changes. That turns one-off AI output into durable runtime structure and addresses some of the biggest weaknesses of coding agents: weak handoffs, fragile memory, and missing long-term verification.

Full docs and install chapter: agentic-nets.com (see also the Install chapter in-repo).

BETA — USE AT YOUR OWN RISK. In active development; may contain bugs, incomplete features, and breaking changes. No warranty. See LICENSE.md and PROPRIETARY-EULA.md.

What's public, what's closed, and who can use it

Agentic-Nets ships as a hybrid stack — licensed public components in this repo plus closed-source Docker Hub images for the core runtime. Read this before deploying.

Layer	What	License	Who can use it
Public components (source in this repo)	agentic-net-gateway, agentic-net-executor, agentic-net-vault, agentic-net-cli, agentic-net-chat, sa-blobstore, agentic-net-tools/, deployment/, monitoring/	BSL 1.1	Free for development, testing, personal, educational, and evaluation use. Commercial production use requires a commercial license. Converts to Apache 2.0 on 2030-02-22.
Closed source (Docker Hub images only — no source in this repo)	alexejsailer/agenticnetos-node, alexejsailer/agenticnetos-master, alexejsailer/agenticnetos-gui	Proprietary EULA	Free for personal, educational, evaluation, and non-commercial use. Commercial use requires contacting alexejsailer@gmail.com.

Both licenses include a strong NO WARRANTY / BETA disclaimer. Nothing here is certified for regulated environments out of the box — you are responsible for your own risk assessment. If you are unsure whether your intended use counts as commercial production, ask before deploying.

---

Problem it solves

Prompts with tools get you started. Production agent systems need more than that: durable state, bounded permissions, visible handoffs, scoped execution, secret management, and a way to replay what happened after the chat has gone away.

Most agent frameworks solve the "how do I call an LLM" problem and leave the operating model to application code. Agentic-Nets makes that operating model explicit: agents read tokens from places, write tokens to places, call only the tools their role permits, and leave an event trail behind.

---

Install in 5 minutes

You need Docker Desktop or Docker Engine with Compose v2, plus one LLM backend: Claude API, OpenAI API, or local Ollama. You do not need Java, Node.js, or Maven unless you want to build services from source.

Apple Silicon Macs can run the current Docker Hub images through Docker Desktop's linux/amd64 emulation. Docker may print platform-mismatch warnings on first start; that is expected unless multi-arch images have been published for your release.

# 1. Clone the public repo
git clone https://github.com/alexejsailer/agentic-nets.git
cd agentic-nets/deployment

# 2. Create your env file
cp .env.template .env

# 3. Edit .env and choose ONE provider:
#    Claude: LLM_PROVIDER=claude + ANTHROPIC_API_KEY=sk-ant-...
#    Ollama: LLM_PROVIDER=ollama (bundled container — no host install required).
#            Default model: deepseek-v4-pro:cloud (routes through ollama.com,
#            requires a one-time login — see step 5). To run fully offline instead,
#            set OLLAMA_MODEL (and the HIGH/MEDIUM/LOW tiers) to a local tag
#            like llama3.2 before starting the stack.
#    OpenAI: LLM_PROVIDER=openai + OPENAI_API_KEY=sk-...

# 4A. Start the full stack with monitoring
docker compose -f docker-compose.hub-only.yml up -d

# 4B. Or start the lighter stack without Grafana/Prometheus/Tempo
# docker compose -f docker-compose.hub-only.no-monitoring.yml up -d

# If startup says port 5001 is already allocated, edit .env and set:
# AGENTICNETOS_REGISTRY_PORT=5002
# Then rerun the same docker compose command.

# 5. If you chose Ollama, authenticate or pull the model into the bundled container:
#    (a) Default cloud model — one-time interactive login (see note below):
docker exec -it agenticnetos-ollama ollama signin
#    (b) OR, if you switched to a local model (e.g. llama3.2), pull it instead:
# docker exec agenticnetos-ollama ollama pull llama3.2

# 6. Optional: seed approved Docker tool images into the local registry.
#    Agents use these for crawler/RSS/search/Reddit/API helper containers.
docker compose -f docker-compose.hub-only.yml --profile tools run --rm agenticos-tool-seeder

# 7. Grab the admin secret the Studio login page asks for.
#    The gateway auto-generates it on first startup and bind-mounts it onto
#    the host — read it from the host (NOT from inside the container):
cat data/gateway/jwt/admin-secret

# 8. Open the Studio GUI and paste the secret into the login page
open http://localhost:4200

Where does the admin secret come from? agentic-net-gateway writes a random admin secret to deployment/data/gateway/jwt/admin-secret on its first start. Read that file on the host and paste the value into the Studio login page (tick Read-only access if you want a read-only JWT — same secret, the gateway mints a scoped token). CLI, chat, and executor mount the same file read-only and auto-acquire their JWTs, so you don't need to configure them. If you prefer a pinned value, set AGENTICOS_ADMIN_SECRET=<long-random-string> in .env before docker compose up -d — that string then becomes the login secret.

Where does the Ollama login token come from? ollama signin is a one-time pairing: it prints a URL + device code to the container logs, you open that URL in a browser, sign in to your ollama.com account, and approve the device. No token file to manage — credentials are stored inside the container at /root/.ollama/ and survive restarts (the ollama-data volume). If you prefer non-interactive auth, generate an API key at ollama.com/settings/keys and pass it: docker exec agenticnetos-ollama ollama signin <your-api-key>. Cloud-suffixed models (:cloud, :671b-cloud, etc.) route through ollama.com and can be rate-limited during long sessions — swap to a local tag if you hit 429 errors.

You don't write any code for the first run. Open the Universal Assistant in the Studio and ask "Help me build my first net." For write operations, switch to or invoke the Workflow Builder persona. It can create places, transitions, arcs, inscriptions, and deploy the result in the active model/session.

Compose choices

File	What it starts	Use it when
deployment/docker-compose.hub-only.yml	Complete local stack from Docker Hub, including monitoring	You want the production-like local setup
deployment/docker-compose.hub-only.no-monitoring.yml	Complete runtime stack from Docker Hub, no monitoring	You want a lighter laptop setup
deployment/docker-compose.yml	Closed-source core images from Docker Hub + public services built locally	You are developing this repo

The .env.template is fully commented. The most important variables are:

Variable	Purpose
AGENTICNETOS_VERSION	Docker Hub image tag. Release CI pins this.
AGENTICNETOS_BIND_ADDRESS	Defaults to 127.0.0.1 so published ports stay local.
LLM_PROVIDER	ollama, claude, openai, claude-code, or codex.
ANTHROPIC_API_KEY, OPENAI_API_KEY	Required only for those hosted providers.
OLLAMA_BASE_URL, OLLAMA_MODEL	Required for local Ollama.
OPENBAO_DEV_ROOT_TOKEN	Local Vault token. Change before exposing the stack.
AGENTICNETOS_NODE_DATA_DIR	Host directory for Node events and snapshots.

Detailed install, env, verification, and troubleshooting: deployment/README.md.

---

Drive it from Claude Code

The agenticos-control Claude Code plugin turns any Claude Code session into a full control surface for a running stack: inspect nets, read and edit places and tokens, call the designtime and runtime REST APIs, fire and diagnose transitions, author nets, drive the Universal Assistant / Persona / Forge personas, and export net diagrams. It is CLI-first (it uses the agenticos CLI when it is installed) with a curl fallback, and works both locally (direct to the services) and remotely (through the gateway's OAuth2, so you can drive the whole thing from anywhere, even your phone).

Install it. From any Claude Code session:

/plugin marketplace add alexejsailer/agentic-nets
/plugin install agenticos-control@agentic-nets

(Working from a local clone instead? /plugin marketplace add ./agentic-nets.)

Point it at your stack. The plugin auto-detects gateway mode when a secret is present, otherwise direct mode. For the local Docker stack (whose gateway is published on 127.0.0.1:8083), reuse the same admin secret the Studio login uses:

export AGENTICOS_GATEWAY_URL=http://localhost:8083
export AGENTICOS_GATEWAY_SECRET_FILE=deployment/data/gateway/jwt/admin-secret

For a same-network setup where master and node are reachable directly, set AGENTICOS_MASTER=http://localhost:8082 and AGENTICOS_NODE=http://localhost:8080 and leave the secret unset. Secrets are read only from an env var or a file, the JWT stays in-process, and nothing is ever printed or written to disk.

Use it. The plugin ships a skill, two agents (agenticos-net-designer, agenticos-net-operator), and slash commands:

Command	What it does
/agenticos-doctor	Preflight the connection (resolved mode/auth/targets + reachability, no secrets)
/agenticos-inspect <modelId> [sessionId] [netId]	Snapshot transitions and states, a session's nets, a net's places and live token counts
/agenticos-fire <modelId> <transitionId>	Fire a transition once (handles the stop/fire/start dance)
/agenticos-persona <universal|persona|...> <modelId> "<prompt>"	Drive a persona and stream its reply
/agenticos-forge <modelId> "<intent>"	Build a reusable tool-net from a plain-language intent
/agenticos-export <modelId> <sessionId> <netId>	Export a net to JSON or PNML (then render a diagram)

Or just describe what you want: the skill routes structural work to the designer agent and diagnosis to the operator agent. Full details, the REST/API reference, and the environment-variable table are in the plugin's own README.

Or connect over MCP — Agentic-Nets as working memory + a net workbench

The agentic-net-mcp server exposes a running stack to any MCP client (Claude Code, Claude Desktop, Cursor, or your own agent framework) over the Model Context Protocol. Where the plugin is a curl/CLI control surface, the MCP server is a native tool protocol — the client calls Agentic-Nets as first-class tools, and gets persistent, structured working memory that keeps working between sessions.

• Memory that runs. memory_write / memory_recall over event-sourced places, with an always-on server-side distiller that turns raw captures into durable notes while you are gone. A SessionStart/SessionEnd hook pair makes it automatic — every Claude Code session starts warm and ends archived, with no discipline required.
• Build and run nets from the client. Deploy starter templates (working-memory, dev-team, brain, watcher), spawn autonomous persona workers that run in parallel server-side, crystallize a session's steps into a replayable zero-LLM tool-net, and even host an llm/agent transition in the client itself using the LLM you already have (e.g. your local claude) — no server-side model required.
• Full platform parity + control. All ~90 tools: the curated ergonomic layer plus the complete native tool catalog, model lifecycle (create_model / list_models), a pause_model kill switch, and a no-logs cockpit (net_stats, diagnose_transition). Scoped to an allowlist, with a gateway-enforced readonly mode.

claude mcp add agenticnets \
  -e AGENTICOS_GATEWAY_URL=http://localhost:8083 \
  -e AGENTICOS_ADMIN_SECRET=$(cat deployment/data/gateway/jwt/admin-secret) \
  -e AGENTICOS_MODELS=my-memory \
  -- npx @agenticnets/mcp

Then just tell your assistant to "remember this" or "set up my working memory". Full tool list, configuration, templates, hooks, and security model are in the server's own README.

---

Release Notes

The active CHANGELOG.md tracks the current calendar quarter. Older quarters are archived under changelogs/ (index).

Quarter	Highlights
Current	CHANGELOG.md
2026 Q2	Gateway/vault maturation, tool-net library + Forge, capability flags, glm-5.2:cloud default — archive
2026 Q1	First releases (v1.6.0 → v1.19.0), repo split, v1.2.0 launch — archive
2025 Q4	Pre-release: distributed execution, agent transitions, outbound-only architecture, designtime API — archive
2025 Q3	Pre-release: project foundations, multi-model architecture, NL→PNML, GUI editor — archive

---

What makes this different

	Prompt-with-tools frameworks	Agentic-Nets
What can this agent see?	Whatever you paste into context	Only the tokens in its inbound places
What can this agent do?	Whatever tools you register	Only tools its role unlocks (r--- → rwxh)
Where do its outputs go?	Back to you, mixed with reasoning	Typed tokens in declared outbound places
What did it actually do?	Chat transcript	Token trail with full provenance
How does it get cheaper?	It doesn't	Crystallization — agent steps collapse into deterministic transitions

The graph gives hallucination less room to become uncontrolled action: inputs, permissions, and outputs are explicit.

---

Architecture

    CLIENT AGENTS  (all authenticate via gateway-minted JWT)
  +--------------+  +--------------+  +--------------+  +---------------+
  | agentic-net  |  | agentic-net  |  | agentic-net  |  | agentic-net   |
  | gui (4200)   |  | cli          |  | chat         |  | executor      |
  | Closed core  |  | Public src   |  | (Telegram)   |  |  (8084)       |
  |              |  |              |  | Public src   |  | Public src    |
  +------+-------+  +------+-------+  +------+-------+  +------+--------+
         |                 |                 |                 |
         | JWT             | JWT             | JWT             | JWT *
         |                 |                 |                 |
         +-----------------+--------+--------+-----------------+
                                    |
                                    | (all client traffic funnels
                                    |  through the gateway;
                                    |  tokens minted from the
                                    |  admin secret auto-generated
                                    |  on first startup at
                                    |  data/gateway/jwt/admin-secret
                                    |  and mounted read-only by
                                    |  cli, chat, executor)
                                    v
                         +-------------------+
                         | agentic-net-      |   Public source (BSL 1.1)
                         | gateway (8083)    |   OAuth2 + JWT router
                         +---+------------+--+
                             |            |
                +------------v+         +-v---------------+
                | agentic-net |         | agentic-net     |   Closed source (Docker Hub)
                | master      |<------->| node            |   orchestration + state engine
                |  (8082)     |         |  (8080)         |
                +--+--------+-+         +-----------------+
                   |        |
                   |        |   BACKEND SERVICES
                   |        |   (master-internal,
                   |        |    not client-exposed)
                   |        |
          +--------v--+  +--v-----------+
          | agentic-  |  | sa-blobstore |   Public source (BSL 1.1)
          | net-vault |  |  (8090)      |   backend data tier
          |  (8085)   |  | large tokens |
          | secrets   |  | + knowledge  |
          +-----------+  +--------------+

  * Executor supports dual-mode polling: JWT via gateway (shown above, works
    across firewalls) OR direct to master on the same compose network.

Agent roles on the wire

Every agent runs under a capability role (rwxhl Unix-style flags):

Flag	Capability	Typical tools available
r	Read	QUERY_TOKENS, LIST_PLACES, GET_NET_STRUCTURE, DESCRIBE_TOOL_NET, discovery
w	Write	+ CREATE_TOKEN, SET_INSCRIPTION, CREATE_NET, TAG_SESSION, REGISTER_TOOL_NET
x	Execute	+ DEPLOY_TRANSITION, START_TRANSITION, FIRE_ONCE, INVOKE_TOOL_NET, DELEGATE_TASK
h	HTTP	+ external HTTP calls
l	Logs	+ event-line observability

Pick minimal. A read-only diagnostic agent gets r----; a full coordinator gets rwxhl. The runtime refuses tool calls outside the configured role.

Executor polling modes

Executor agents use egress-only polling — firewall-friendly, deployable anywhere:

Mode	When	Executor polls	Auth
Direct	Same network as master	http://agentic-net-master:8082	None (internal)
Gateway	Remote / different network	http://<gateway-host>:8083	JWT (auto-acquired)

Public services (this repo)

Service	Purpose	Port
agentic-net-gateway	OAuth2 API gateway with JWT auth, rate limits, read-only scopes	8083
agentic-net-executor	Distributed command execution agent, polls master direct or via gateway	8084
agentic-net-vault	Secrets management (OpenBao wrapper) for agent-transition credentials	8085
agentic-net-cli	Command-line agent with multi-provider LLM routing and tool-catalog sync	—
agentic-net-chat	Telegram-facing agent with streaming tool-call batches and /verbose toggle	—
sa-blobstore	Distributed blob storage for large tokens, artifacts, and knowledge content	8090
agentic-net-tools/	Tool containers agents start on demand (crawler, echo, reddit, rss, search, secured-api)	dynamic

Docker tools are published as alexejsailer/agenticos-tool-*:<version> and mirrored into the bundled local registry (localhost:5001) by agenticos-tool-seeder. Master only runs images matching the local allowlist, normally localhost:5001/agenticos-*.

Closed-source services (Docker Hub)

Image	Purpose	Port
alexejsailer/agenticnetos-node	Event-sourced state engine, tree-structured persistence, ArcQL queries	8080
alexejsailer/agenticnetos-master	Orchestration, LLM integration, transition engine, agent runtime	8082
alexejsailer/agenticnetos-gui	Angular visual editor with drag-drop Petri-net design	4200

These images are governed by the Proprietary EULA.

Full architecture deep dive: see ARCHITECTURE.md. Long-form whitepaper — The Harness Control System: Complete Domain Automation on Agentic-Nets (concepts, control loop, use cases, live evidence): docs/whitepaper/the-harness-control-system.html — a self-contained HTML document; download and open in any browser, or view it rendered.

---

Repository structure

agentic-nets/
├── LICENSE.md                    # BSL 1.1 for public code in this repo
├── PROPRIETARY-EULA.md           # EULA for Docker Hub images
├── README.md                     # (this file)
├── ARCHITECTURE.md               # Deep dive: transitions, ArcQL, coordination
├── CHANGELOG.md                  # Human-curated release notes
├── CONTRIBUTING.md               # How to contribute
│
├── docs/
│   ├── foundations/              # Figures from the 2012 KIT diploma thesis (see FOUNDATIONS.md)
│   └── whitepaper/               # The Harness Control System — self-contained HTML whitepaper
│
├── agentic-net-gateway/          # OAuth2 API gateway (Spring Boot)
├── agentic-net-executor/         # Command executor (Spring Boot)
├── agentic-net-vault/            # Secrets wrapper for OpenBao (Spring Boot)
├── agentic-net-cli/              # CLI agent (TypeScript/Node)
├── agentic-net-chat/             # Telegram-facing agent (TypeScript/Node)
├── sa-blobstore/                 # Distributed blob storage (Spring Boot)
├── agentic-net-tools/            # Tool containers (Docker)
│
├── deployment/
│   ├── README.md                 # Local Docker Compose install guide
│   ├── docker-compose.yml        # Hybrid: Hub images + local builds
│   ├── docker-compose.hub-only.yml  # All services from Docker Hub + monitoring
│   ├── docker-compose.hub-only.no-monitoring.yml  # Runtime stack without monitoring
│   ├── .env.template             # Environment config template
│   ├── dockerfiles/              # Build files for public services
│   └── scripts/
│       ├── build-and-push.sh     # Build & push public service images
│       └── seed-tool-registry.sh # Mirror/build Docker tools into local registry
│
└── monitoring/
    ├── config/                   # OTel, Prometheus, Tempo configs
    └── grafana-provisioning/     # Dashboards and datasources

---

Licensing

Dual-license model:

• Public code in this repo — BSL 1.1. Free for development, testing, personal, educational, and evaluation use. Commercial production use requires a commercial license. Converts to Apache 2.0 on 2030-02-22.
• Closed-source Docker Hub images (agenticnetos-node, agenticnetos-master, agenticnetos-gui) — Proprietary EULA. Free for personal, educational, evaluation, non-commercial use. Commercial use requires contact at alexejsailer@gmail.com.

ALL SOFTWARE IS PROVIDED AS-IS WITH ABSOLUTELY NO WARRANTY.

---

Contact

• Commercial licensing: alexejsailer@gmail.com
• Website & blog: https://alexejsailer.com
• Hosted docs: https://agentic-nets.com
• Video walkthroughs (YouTube): Agentic-Nets playlist
• Issues: https://github.com/alexejsailer/agentic-nets/issues
• Contributing: see CONTRIBUTING.md

---

Much of this codebase was built with AI pair programming. Commits co-authored by Claude Opus 4.7 (1M context) are part of that story — it felt right for a governed multi-agent runtime to be built, in part, by agents. See CHANGELOG.md for the human-curated release notes.

Copyright (c) 2025-2026 Alexej Sailer. All rights reserved.