
Ag2 Network Quickstart
- 30 installs
- 8 repo stars
- Updated July 27, 2026
- ag2ai/ag2-skills
ag2-network-quickstart is a Claude Code skill that builds a multi-agent AG2 beta network with a central Hub, agent registration, and channel adapters.
About
This skill builds a multi-agent AG2 beta network, the standard multi-agent pattern in autogen.beta, activated whenever two or more Agents need to interact. It covers Hub.open, LocalLink, HubClient.register, Passport, Resume, the channel lifecycle, and the two 2-party channel adapters (consulting for strict question-and-reply and conversation for free-form). It is the entry point that routes to the discussion, workflow, governance, and tools-and-views skills.
- Builds a multi-agent AG2 network: Hub, HubClient.register, and channels
- The standard multi-agent pattern in autogen.beta
- Entry point that routes to discussion, workflow, governance, and tools skills
Ag2 Network Quickstart by the numbers
- 30 all-time installs (skills.sh)
- Ranked #9,276 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 1, 2026 (Skillselion catalog sync)
ag2-network-quickstart capabilities & compatibility
Free skill; requires an LLM provider API key to run the agents.
- Capabilities
- multi agent network · agent registration · channel lifecycle · agent orchestration
- Use cases
- orchestration
- Pricing
- Bring your own API key
What ag2-network-quickstart says it does
The network turns a collection of `Agent` instances into a coordinated multi-agent system.
The network is **opt-in**. Bare `Agent` continues to work standalone
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| Installs | 30 |
|---|---|
| repo stars | ★ 8 |
| Last updated | July 27, 2026 |
| Repository | ag2ai/ag2-skills ↗ |
What it does
Set up a multi-agent AG2 network so two or more registered agents can interact through a central hub.
Who is it for?
Developers setting up a multi-agent system or replacing the classic GroupChat / handoffs pattern.
Skip if: One agent spawning its own sub-tasks, which uses ag2-subagent-delegation instead.
When should I use this skill?
The user wants two or more agents to interact, a multi-agent chat, or an agent registry / audit trail.
What you get
A central Hub holds registry, audit log, and channels so agents interact observably and replayably.
By the numbers
- channel lifecycle has 4 states (PENDING to ACTIVE to CLOSING to CLOSED)
- 2 built-in 2-party adapters (consulting, conversation)
Files
AG2 Network — Quickstart
The network turns a collection of Agent instances into a coordinated multi-agent system. A central Hub holds authoritative state (registry, audit log, write-ahead logs per channel); each agent lives behind a thin AgentClient that connects through a HubClient. Every send goes through the hub, so every interaction is replayable and observable.
The network is opt-in. Bare Agent continues to work standalone — the network only activates when you import from autogen.beta.network.
When to use
Load this skill whenever the user wants two or more agents to interact. Concrete trigger phrases:
- "Have two agents talk to each other"
- "Set up a multi-agent system / multi-agent chat / agent network"
- "Agents that can call each other"
- "Replace the classic
GroupChat/ConversableAgent.handoffs" - "Add a registry / audit trail / shared inbox for my agents"
Not a network task: if the user is asking one agent to spawn its own sub-tasks (recursive task fan-out, parallel sub-task execution), use ag2-subagent-delegation instead. The network is for distinct, registered agents collaborating.
Mental model
┌────────────────┐
│ Hub │ ←── audit log, registry, channels,
│ ── adapters ── │ WAL, sweepers, expectation
│ ── channels ── │ evaluators
│ ── audit log ──│
└────────┬───────┘
│ in-process duplex (LocalLink)
┌──────────────────┼──────────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│AgentClient│ │AgentClient│ │AgentClient│
│ alice │ │ bob │ │ carol │
│ Agent │ │ Agent │ │ Agent │
└──────────┘ └──────────┘ └──────────┘| Concept | Lives in | Purpose |
|---|---|---|
Hub | One per network | Authoritative state — registry, audit log, channel table, WAL, sweepers |
Passport | Hub registry | Stable identity (name, hub-stamped agent_id, optional owner, model) |
Resume | Hub registry | Capability claims plus hub-mutated observed track record |
HubClient | One per process | Per-process broker; manages registration |
AgentClient | One per registered Agent | Wraps the Agent; sends envelopes, runs the notify handler |
Envelope | The wire format | Hub-stamped record of one event in one channel |
Channel | Created by agent_client.open(...) | A bounded multi-party exchange governed by an adapter |
The hub assigns the agent_id at registration. Use it (alice.agent_id) for routing rather than the human-readable name.
The smallest possible network
A single-process hub, two agents, a consulting channel (strict 1Q1R, auto-closes after the reply):
import asyncio
from autogen.beta import Agent
from autogen.beta.config import AnthropicConfig
from autogen.beta.knowledge import MemoryKnowledgeStore
from autogen.beta.network import (
EV_CHANNEL_CLOSED,
EV_TEXT,
Hub,
HubClient,
LocalLink,
Passport,
Resume,
)
async def main() -> None:
config = AnthropicConfig(model="claude-sonnet-4-6")
# 1. Boot the hub. MemoryKnowledgeStore for in-process; DiskKnowledgeStore(path)
# for durability across restarts.
hub = await Hub.open(MemoryKnowledgeStore(), ttl_sweep_interval=0)
link = LocalLink(hub) # in-process duplex transport
# 2. One HubClient per process boundary; here we use two for clarity.
alice_hc = HubClient(link, hub=hub)
bob_hc = HubClient(link, hub=hub)
# 3. Register each Agent. The hub stamps the agent_id and returns an AgentClient.
# attach_plugin=False gives a bare agent (no peers/channels/tasks/context/
# delegate tools) — fine here since alice & bob just send/reply. The `say`
# tool is offered per-turn by the adapter, not the plugin (see below).
alice = await alice_hc.register(
Agent("alice", prompt="Ask one focused question and stop.", config=config),
Passport(name="alice"),
Resume(),
attach_plugin=False,
)
bob = await bob_hc.register(
Agent("bob", prompt="Answer in one short sentence.", config=config),
Passport(name="bob"),
Resume(),
attach_plugin=False,
)
# 4. Open a consulting channel. The adapter posts EV_CHANNEL_INVITE to bob,
# bob's default handler auto-acks, channel goes ACTIVE.
channel = await alice.open(type="consulting", target="bob")
await channel.send(
"What's the single most important property of a distributed system?",
audience=[bob.agent_id],
)
# 5. Bob's default handler probes can_send, runs Agent.ask on the inbound
# text, sends the reply. ConsultingAdapter sees both flags set and
# auto-closes with reason "consulting_complete".
close_env = await alice.wait_for_channel_event(
channel_id=channel.channel_id,
predicate=lambda e: e.event_type == EV_CHANNEL_CLOSED,
timeout=60.0,
)
print(f"closed: {close_env.event_data.get('reason')!r}")
# 6. Replay the conversation from the hub's WAL.
wal = await hub.read_wal(channel.channel_id)
for env in wal:
if env.event_type == EV_TEXT:
speaker = "alice" if env.sender_id == alice.agent_id else "bob"
print(f"{speaker}: {env.event_data['text']}")
await alice_hc.close()
await bob_hc.close()
await hub.close()
asyncio.run(main())That's the entire mandatory surface. Everything else below is variation.
Picking a channel adapter
Every channel is governed by an adapter that defines participants, turn order, and termination. Four adapters ship; pick one when you call agent_client.open(type=..., target=...).
| Adapter | Participants | Turn order | Termination | Default view |
|---|---|---|---|---|
consulting | Exactly 2 | Strict 1Q1R (initiator → respondent) | Auto-closes after respondent's reply | FullTranscript() |
conversation | Exactly 2 | Free-form (either side, any time) | Explicit channel.close() or TTL | WindowedSummary(recent_n=10) |
discussion | 2+ | Round-robin via ordering="round_robin" | Explicit close or TTL | WindowedSummary(recent_n=N*2) |
workflow | 2+ | Declarative TransitionGraph | Graph terminates (TerminateTarget / max_turns) | WindowedSummary(recent_n=N*2) |
This skill covers `consulting` and `conversation` (the 2-party adapters). For the others:
- N-party round-robin → load `ag2-network-discussion`.
- Declarative orchestration with
TransitionGraph, conditional handoffs, or migrating from classicGroupChat→ load `ag2-network-workflow`.
Plugin tools vs. adapter tools — attach_plugin and say
HubClient.register(...) attaches NetworkPlugin by default. The plugin contributes the identity-level cross-cutting tools — peers / channels / tasks / context / delegate — and nothing channel-specific. Channel-specific tools (notably say, which posts a text envelope into the channel) are offered per turn by the channel's adapter via adapter.tools_for(...), regardless of attach_plugin:
| Adapter | Offers say? |
|---|---|
consulting | only to the participant whose turn it is in the 1Q1R |
conversation | always (no turn order) |
discussion | only to expected_next_speaker |
workflow | never — routing is your @tool handoff functions |
So attach_plugin=False no longer means "no say" — it means "no delegate / peers / channels / tasks / context". Pass it for a bare agent (tests, pure pipeline workers); keep the default if the agent needs those cross-cutting verbs.
You normally don't need to think about say at all: the default handler always posts the round-end envelope from the agent's plain reply, so an agent that just answers is fine. say is for the rare cases of posting an extra message in a turn, or posting into a different channel the agent is also in. (Edge case to avoid: an agent on a consulting channel that calls say(...) and also returns a non-empty reply double-sends — the second envelope trips channel is closed on the strict 1Q1R adapter. If you don't want the agent calling say, just don't prompt it to.) Full detail: ag2-network-tools-and-views → "Adapter-owned tools (tools_for)".
consulting — strict 1Q1R
The example above. Initiator sends exactly one substantive envelope; respondent sends exactly one reply; the adapter auto-closes with event_data["reason"] == "consulting_complete".
State on the hub side:
@dataclass(slots=True)
class ConsultingState:
initiator_sent: bool = False
respondent_replied: bool = FalseConsultingAdapter.validate_send rejects:
- Out-of-order sends (respondent speaking before initiator's first envelope).
- Any send after both flags are set — raises
ProtocolError, propagated back to the caller'schannel.send(...).
Default expectations are strict: acks_within(30s, auto_close) and reply_within(600s, auto_close). If the respondent doesn't ack the invite within 30s, or doesn't reply within 10 minutes, the hub auto-closes with "expectation_violated:acks_within" or "expectation_violated:reply_within". Tune these via ag2-network-governance.
conversation — free-form 2-party
Either side sends at any time, any order. The adapter never auto-closes; you halt via channel.close() or rely on TTL.
channel = await alice.open(type="conversation", target="bob")
await channel.send("Hi bob, what's a good first ML concept to learn?")Both default handlers run Agent.ask on every inbound EV_TEXT, so once started the conversation auto-drives. Two halt patterns:
1. Application-side cap — poll the WAL until you've seen N text envelopes, then await channel.close(). 2. Empty reply as halt signal — the default handler treats an empty body as "don't send", so an LLM that replies with "" ends the chain. Pair with a prompt like "reply with empty string when you have nothing useful to add".
ConversationAdapter.validate_send only checks "is the sender a participant?" — same-side sends in a row are allowed because the adapter doesn't model turn order.
Default expectation is lenient: max_silence(3600s, audit) (logs to the audit kind AUDIT_KIND_EXPECTATION_VIOLATED but does not close).
Use `conversation` when: two specialists genuinely converse without a fixed order (analyst ↔ critic); chat UIs where your application controls the stop signal.
Don't use `conversation` for: strict 1Q1R (use consulting); multi-participant chats (use discussion or workflow).
A non-LLM participant — HumanClient
Not every participant is an Agent. HumanClient is a network member with no LLM, no NetworkPlugin, no assembly policies — a person at a UI, a bridge to another system, or a scripted "user" that seeds a channel. Register it with register_human (not register — that path now rejects kind="human" and points you here):
from autogen.beta.network import HumanClient, Passport
user_hc = HubClient(link, hub=hub)
user = await user_hc.register_human(Passport(name="user", kind="human")) # resume=, rule=, auto_ack_invites= optionalIt implements the same NetworkClient surface as AgentClient for outbound — user.open(type=..., target=...), user.send(channel_id, text, audience=...), user.post_envelope(env) (the escape hatch for adapter-shaped envelopes like a workflow EV_PACKET) — and gives you two ways to consume inbound envelopes:
- Push —
user.on_envelope(callback); the coroutine fires once per inbound envelope. Multiple callbacks compose; a raising callback is logged, never propagated. - Pull —
await user.next_envelope(predicate=..., timeout=...)blocks for the next match;async for env in user.envelopes(): ...streams everything untiluser.disconnect().
It auto-acks channel invites (auto_ack_invites=True default) so the hub's join handshake completes without UI round-trips; pass auto_ack_invites=False to gate joins yourself. Discover humans via hub.list_agents(kind="human").
Common uses: the kickoff seeder for a workflow channel (FromSpeaker(user) → AgentTarget(first_agent) — see ag2-network-workflow), the human leg of a consulting Q&A, or a participant in a discussion round-robin. The agent-side surface (custom handlers, headless workers, gateways) is in ag2-network-tools-and-views.
Identity — Passport and Resume
Three dataclasses describe an agent on the network. Tenant supplies most fields; the hub stamps the rest.
from autogen.beta.network import Passport, Resume, ResumeExample
passport = Passport(
name="alice", # required, unique within the hub
owner="acme", # optional, tenant id for multi-tenant deployments
model="claude-sonnet-4-6", # optional, surfaces on peer-lookup results
kind="agent", # optional: "agent" (default / None) | "human" | "remote_agent"
)
resume = Resume(
claimed_capabilities=["analysis", "policy"],
domains=["finance"],
summary="Senior policy analyst — scenario synthesis and rebuttal review.",
examples=[ResumeExample(title="Q3 risk brief", note="…")],
)The hub stamps Passport.agent_id and Passport.created_at at registration. Passport.kind (type alias PassportKind) discriminates participant types — None/"agent" for the usual LLM-backed AgentClient, "human" for a HumanClient (use register_human, not register), "remote_agent" reserved for A2A/federation. hub.list_agents(kind=...) filters by it. The Resume.observed field (per-capability ObservedStat counts) is hub-mutated as the agent runs capability-tagged tasks — see ag2-network-governance for how to wire that up.
For the smallest case you can pass Passport(name="alice") and Resume() and call it done.
Channel lifecycle
agent_client.open(type=..., target=...)
│
▼
PENDING ──┬─ all targets ack ──→ ACTIVE ──┬─ adapter terminates ──→ CLOSED
│ │
└─ ack timeout ──→ CLOSED └─ explicit channel.close() ──→ CLOSING ──→ CLOSED
(invite_timeout) or TTL expiredThe default invite_ack_timeout on Hub.open(...) is 30s; if any invited target doesn't ack within that window, create_channel raises ProtocolError and the channel goes straight to CLOSED with reason "invite_timeout". (The separate expectation-sweeper path — the acks_within expectation — auto-closes with "expectation_violated:acks_within" instead; see the consulting section below.)
Sending an envelope
await channel.send(text, audience=[bob.agent_id])audience controls who sees the envelope (default: all participants). The hub stamps Envelope.envelope_id, sender_id, created_at, and writes it to the WAL.
For custom event types, send raw envelopes via agent_client.send_envelope(envelope). The full Envelope shape and the EV_* event constants are documented in ag2-network-tools-and-views.
The five channel-close routes
Every channel terminates with an EV_CHANNEL_CLOSED envelope. Five routes lead there; pick by who decides:
| Pattern | Who decides | Best for |
|---|---|---|
channel.close(reason=...) | Your orchestration code | Custom caps (turn count, time, predicate) |
Agent-side tool (ChannelInject) | The LLM | "Agent decides we're done" |
| Adapter sentinel (subclass) | The framework | Content-based stop ("TERMINATE" keyword) |
Workflow TerminateTarget | A declarative graph | Multi-step orchestrations |
| TTL / expectations | The hub's sweepers | Time- or expectation-based safety nets |
Adapter compatibility:
| Auto-close | App close | Agent tool | Sentinel | Workflow graph | |
|---|---|---|---|---|---|
consulting | Yes (after reply) | Yes (early bail) | Yes | Subclass | n/a |
conversation | Never | Yes (typical) | Yes | Canonical | n/a |
discussion | Never | Yes (typical) | Yes | Subclass | n/a |
workflow | Yes (graph) | Yes (override) | Yes (via ToolCalled) | n/a | Canonical |
Pattern: agent-side close tool
The LLM decides when to stop. Inject the active Channel into the tool:
from autogen.beta.network.client.inject import ChannelInject
async def end_conversation(reason: str, channel: ChannelInject) -> str:
"""Close the active channel. The reason flows on EV_CHANNEL_CLOSED."""
if channel is None:
return "no active channel"
await channel.close(reason=f"agent_close:{reason}")
return f"closed: {reason}"
alice_agent.tool(end_conversation)
bob_agent.tool(end_conversation)The default handler stamps the active Channel into context.dependencies before each LLM turn, so ChannelInject resolves automatically. Outside a network turn it resolves to None — the guard above keeps the tool safe in non-network contexts.
Prefer the tool-call pattern over an adapter sentinel ("TERMINATE" keyword) — tool calls are typed, traceable on the WAL, multilingual, and resist prompt injection.
Watching for close
All five routes produce the same EV_CHANNEL_CLOSED envelope, so observers only need one predicate:
close_env = await alice.wait_for_channel_event(
channel_id=channel.channel_id,
predicate=lambda e: e.event_type == EV_CHANNEL_CLOSED,
timeout=180.0,
)
print(f"reason: {close_env.event_data.get('reason')!r}")ChannelMetadata.close_reason is also stored on the channel record — await hub.get_channel(channel_id) returns the reason without re-reading the WAL.
Replay and inspection
The hub's WAL is the single source of truth for "what happened in this channel":
wal = await hub.read_wal(channel.channel_id)
for env in wal:
print(env.created_at, env.event_type, env.sender_id, env.event_data)Every envelope is hub-stamped (envelope_id, created_at, sender_id, audience, event_type, event_data). The WAL is keyed by channel id; reading it works for any channel this process can see.
For the audit log (hub-level events: agent registered, channel created/closed, expectation violated), see ag2-network-governance.
Closing down
await alice_hc.close()
await bob_hc.close()
await hub.close()Always pair Hub.open(...) with hub.close() (typically in try/finally). hub.close() cancels the sweeper tasks, closes the underlying store, drains pending I/O. HubClient.close() cancels the link's listening task and unsubscribes the clients.
What to load next
| User goal | Skill |
|---|---|
| N-party round-robin / fixed turn order | ag2-network-discussion |
Declarative orchestration / TransitionGraph / GroupChat migration | ag2-network-workflow |
| Rate limits, access policy, expectations, audit, capability tracking, swappable arbiter / hub listeners | ag2-network-governance |
Adapter-owned tools (say / tools_for), plugin tools (delegate / peers / …), custom handlers, HumanClient internals, views, peer discovery | ag2-network-tools-and-views |
Quick reference — imports
from autogen.beta.network import (
# Hub + transport
Hub,
HubClient,
LocalLink,
# Participants
HumanClient, # register via HubClient.register_human(...)
# Identity
Passport,
PassportKind, # Literal["agent", "human", "remote_agent"] | None
Resume,
ResumeExample,
# Envelopes + events
Envelope,
EV_TEXT,
EV_CHANNEL_INVITE,
EV_CHANNEL_INVITE_ACK,
EV_CHANNEL_OPENED,
EV_CHANNEL_CLOSED,
EV_CHANNEL_EXPIRED,
Priority,
# Errors
AccessDeniedError,
InboxFull,
ProtocolError,
)
from autogen.beta.knowledge import MemoryKnowledgeStore # or DiskKnowledgeStoreRelated skills
FAQ
What are the two 2-party channel adapters?
consulting for strict one-question-one-reply and conversation for free-form.
Is the network required for a single agent?
No, the network is opt-in; a bare Agent still works standalone.