Bring your agents
Connect ChatGPT, Claude, Codex, OpenClaw, or any MCP client to the same company context, scoped to each user.
Connect an agent →Summarize new board memos: what was approved, what is blocked, and who owns each next action.
See how initiatives, decisions, owners, and follow-through connect across the organization.
Connectors stream your databases, SaaS tools, files, devices, and internal APIs into context. Your systems of record stay where they are. Models, sandboxes, and devices are independent layers, credentials gateway-side. Flip the tabs to wire each one.
Connectors ↗Raw events resolve into people, customers, projects, policies, and goals, with the relationships between them. Every fact from the connectors above converges on the right record, carries its provenance, and is read under the caller's permissions.
Memory ↗A trigger — a schedule, or reactive to connector events — plus a plain-language prompt. Once defined it runs unprompted: scans memory, matches the trigger, and surfaces the work with the evidence attached.
Automations ↗“On every new , watch and for follow-ups on its . When an is blocked, flag it and ping the who owns the before the next review.”
ChatGPT, Claude, and Codex connect over MCP; Slack, Teams, and WhatsApp over chat; your own apps over the API. Same context, same permissions, whoever's asking. Consequential work arrives as a proposal you review, edit, and approve.
Platforms ↗Action needed · Board Q4
Drafted the exec digest with owners. Review before I post it:
Use the agents your team already trusts. Managed agents are optional.
Connect ChatGPT, Claude, Codex, OpenClaw, or any MCP client to the same company context, scoped to each user.
Connect an agent →Run repeatable work from live events or schedules under the same approval policy.
Build a managed agent →Share context, permissions, approvals, and connected actions with any agent. Add Lobu's runtime only when you need it.







The use case above is one project: connections, entity types, automations, and agent configuration. Inspect each piece or let your coding agent generate it.
import {
connectorFromFile,
defineAgent,
defineConfig,
defineSkill,
defineEntityType,
defineRelationshipType,
defineAutomation,
every,
secret,
field,
} from "@lobu/cli/config";
import type LinearCyclesConnector from "./linear-cycles.connector.ts";
const boardActionTrackerSkill = defineSkill({
name: "board-action-tracker",
content:
"Track board action items: check task delivery status, blocker resolution progress, and approaching deadlines for the next board packet.\n",
});
const leadership = defineAgent({
id: "leadership",
skills: [boardActionTrackerSkill],
name: "leadership",
description:
"Help leadership teams turn memos, decisions, and board materials into reusable operating context",
dir: ".",
providers: [
{
id: "anthropic",
model: "claude/sonnet-4-5",
key: secret("ANTHROPIC_API_KEY"),
},
],
network: {
allowed: [
"github.com",
".github.com",
".githubusercontent.com",
"registry.npmjs.org",
".npmjs.org",
],
},
});
// entity types and relationships defined here…
const boardActionTracker = defineAutomation({
agent: leadership,
slug: "board-action-tracker",
name: "Board action tracker",
triggers: [every("0 8 * * *")],
tags: ["leadership", "daily", "board"],
agentKind: "notifier",
skills: ["board-action-tracker"],
});
export default defineConfig({
connectors: [
connectorFromFile<typeof LinearCyclesConnector>(
"./linear-cycles.connector.ts"
),
],
org: "leadership",
orgName: "Leadership",
orgDescription:
"Turn memos, decisions, and board materials into reusable operating context",
agents: [leadership],
entities: [decision, document, region, risk, task],
relationships: [approved, assigned, blockedBy],
automations: [boardActionTracker],
});Connect any agent to shared context and keep consequential actions under approval.