## Thinking Path > - Paperclip is the open source app people use to manage AI agents for work > - Its web UI keeps live views (issue threads, run transcripts, dashboard) fresh via React Query polling plus a live-events websocket, coordinated across tabs with a `BroadcastChannel` layer > - Long-lived tabs viewing live agent runs grew to multi-GB memory footprints while their JS heap stayed ~60–200 MB — so the memory is off-heap (Blink/native + committed allocator arenas), not a classic JS leak > - Live profiling of a reproduced 2.7 GB / 66 MB tab showed 15–30% idle CPU, ~3 fetches/sec across overlapping poll loops, and ~8 `setInterval` create/clear cycles per second whose rate grew ~7× as the tab aged — relentless allocation churn that inflates committed memory the OS never reclaims, amplified across tabs by the cross-tab fan-out > - This pull request cuts that churn at its four largest sources (invalidation storm, per-instance 1 s timers, redundant polling, unbounded streamed-run set) > - The benefit is that idle tabs do far less periodic work, so their off-heap footprint stops ballooning over a long session ## Linked Issues or Issue Description No public GitHub issue exists; describing inline per CONTRIBUTING.md → "Link Issues or Describe Them In-PR", following the bug report template. **What happened?** Browser tabs viewing live agent runs grew to 8–16 GB memory footprint over a long session (multiple tabs open), while each tab's "live" JS heap stayed only ~150–250 MB. Every idle tab also burned 15–30% CPU. Tabs eventually approached the ~4 GB V8 heap ceiling / OS pressure and could crash. **Expected behavior** Tabs viewing live runs should hold a bounded footprint and do minimal work while idle, regardless of how long they stay open or how many tabs are open. **Steps to reproduce** Open several issue/run tabs that have agents actively streaming and leave them open for a while. Watch Chrome's Task Manager: Memory Footprint climbs into the GBs while "JavaScript Memory" stays small, and CPU stays high on idle tabs. Reproduced in ~90 minutes: a tab reached 2.7 GB footprint on a 66 MB JS heap, and the per-second timer-churn rate was ~7× higher on a 90-minute-old tab than a fresh one. **Paperclip version or commit** Branch `fix/live-updates-churn`, off `master`. **Deployment mode** Local dev (`pnpm dev`), web UI. Not adapter-specific — core UI live-updates plumbing (observed with `claude_local` / `codex_local` runs). ## What Changed - **`ui/src/lib/query-invalidation-batcher.ts` (new)** — `createInvalidationBatcher` throttles + de-dupes React Query invalidations into one flush per ~300 ms, and `createCoalescingQueryClient` wraps the client via a `Proxy` so only `invalidateQueries` is batched (optimistic `setQueryData` writes stay immediate). Wired into `LiveUpdatesProvider`, which previously invalidated synchronously on every websocket event. - **`ui/src/hooks/useSecondTick.ts` (new)** — one shared, ref-counted, page-wide 1 s ticker. `useLiveElapsed` in `IssueChatThread` now uses it instead of a per-instance `setInterval` that forced a full-thread re-render every second per live element. - **`ui/src/components/transcript/useLiveRunTranscripts.ts`** — when the realtime websocket is enabled, the recurring log poll backs off to a 30 s safety-net cadence instead of polling every 2 s on top of the live stream. Added a marker for the durable poll→push rearchitecture. - **`ui/src/lib/issueChatTranscriptRuns.ts`** — `resolveIssueChatTranscriptRuns` now caps the streamed run set (live/active runs always kept; most-recent linked runs fill up to 20) so a large run history can't open a live-transcript poll per historical run. - **`ui/src/main.tsx`** — explicit `gcTime` so cross-tab-published cache entries for unobserved resources are collected promptly. - Tests for the batcher, shared ticker, and run cap. ## Verification - `vitest`: new suites `query-invalidation-batcher.test.ts` (batcher collapses 20 invalidations → 1 flush; keeps distinct keys/variants; dispose cancels; proxy passes non-invalidate methods through), `useSecondTick.test.tsx` (single ref-counted timer, stops when idle), `issueChatTranscriptRuns.test.ts` (cap keeps newest + live). All pass. - Existing affected suites pass: `LiveUpdatesProvider` (23), `IssueChatThread` (), `useLiveRunTranscripts`, `AgentDetail.instructions` — 109 tests across affected files. - `tsc -b` clean. - Behavior confirmed by live profiling before the change (2.7 GB / 66 MB tab, ~8 interval churns/sec growing 7× with age). Runtime churn reduction should be re-measured against a rebuilt bundle with the same instrumentation. ## Risks Low-to-moderate; all changes reduce work rather than add features. - **Invalidation batching** delays live-driven refetches by up to ~300 ms. Optimistic `setQueryData` writes (e.g. the visible issue's new comment) remain immediate, so foreground updates still feel instant; only the safety-net refetch is throttled. Non-live invalidations (user actions, mutations) are unaffected — they use the real client. - **Poll back-off** relies on the websocket as the live source when realtime is enabled; a 30 s fallback poll still covers gaps/reconnects (both the transcript hook and `LiveUpdatesProvider` also auto-reconnect). - **Run cap (20)** means an issue with a very large run history streams live transcripts only for its live/active + 20 most-recent runs; older runs still open normally via their run pages. - Downstream test fallout (timing-sensitive tests around invalidation/polling) may need adjustment — flagged intentionally for follow-up. Durable follow-up (out of scope, marked in code): replace transcript/run polling with server push (SSE/websocket deltas) so idle tabs do no periodic work at all. ## Model Used - **Provider:** Anthropic, via the Claude Code CLI. - **Model:** Claude Opus 4.8 (`claude-opus-4-8`). - **Reasoning mode:** Extended thinking enabled. - **Capabilities used:** tool use (shell, file editing), sub-agent fan-out for codebase analysis, and the Chrome DevTools MCP to reproduce and profile the memory/CPU churn on a live instance. ## Checklist - [x] I have included a thinking path that traces from project context to this change - [x] I have specified the model used (with version and capability details) - [x] I have checked ROADMAP.md and confirmed this PR does not duplicate planned core work (a bug/perf fix, not planned core feature work) - [x] I have searched GitHub for duplicate or related PRs and linked them above (none found) - [x] I have either (a) linked existing issues with `Fixes: #` / `Closes #` / `Refs #` OR (b) described the issue in-PR following the relevant issue template - [x] I have not referenced internal/instance-local Paperclip issues or links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip` URLs) - [x] My branch name describes the change (e.g. `docs/...`, `fix/...`) and contains no internal Paperclip ticket id or instance-derived details - [x] I have run tests locally and they pass - [x] I have added or updated tests where applicable - [x] I have considered and documented any risks above - [ ] I have updated relevant documentation to reflect my changes (N/A — no user-facing docs; rationale documented inline) - [x] All Paperclip CI gates are green - [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups - [x] I will address all Greptile and reviewer comments before requesting merge 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Quickstart · Docs · GitHub · Discord · Twitter · Website
Paperclip is the app people use to manage AI agents for work.
Open-source orchestration for teams of AI agents.
If OpenClaw is an employee, Paperclip is the company.
Paperclip is a Node.js server and React UI that orchestrates a team of AI agents to run a business. Bring your own agents, assign goals, and track work and costs from one dashboard.
It looks like a task manager. Under the hood: org charts, budgets, governance, goal alignment, and agent coordination.
Manage business goals, not pull requests.
| Step | Example | |
|---|---|---|
| 01 | Define the goal | "Build the #1 AI note-taking app to $1M MRR." |
| 02 | Hire the team | CEO, CTO, engineers, designers, marketers — any bot, any provider. |
| 03 | Approve and run | Review strategy. Set budgets. Hit go. Monitor from the dashboard. |
Paperclip is right for you if
- ✅ You want to build autonomous AI companies
- ✅ You coordinate many different agents (OpenClaw, Codex, Claude, Cursor) toward a common goal
- ✅ You have 20 simultaneous Claude Code terminals open and lose track of what everyone is doing
- ✅ You want agents running autonomously 24/7, but still want to audit work and chime in when needed
- ✅ You want to monitor costs and enforce budgets
- ✅ You want a process for managing agents that feels like using a task manager
- ✅ You want to manage your autonomous businesses from your phone
Features
🔌 Bring Your Own AgentAny agent, any runtime, one org chart. If it can receive a heartbeat, it's hired. |
🎯 Goal AlignmentEvery task traces back to the company mission. Agents know what to do and why. |
💓 HeartbeatsAgents wake on a schedule, check work, and act. Delegation flows up and down the org chart. |
💰 Cost ControlMonthly budgets per agent. When they hit the limit, they stop. No runaway costs. |
🏢 Multi-CompanyOne deployment, many companies. Complete data isolation. One control plane for your portfolio. |
🎫 Ticket SystemEvery conversation traced. Every decision explained. Full tool-call tracing and immutable audit log. |
🛡️ GovernanceApprove hires, override strategy, pause or terminate any agent — at any time. |
📊 Org ChartHierarchies, roles, reporting lines. Your agents have a boss, a title, and a job description. |
📱 Mobile ReadyMonitor and manage your autonomous businesses from anywhere. |
Problems Paperclip solves
| Without Paperclip | With Paperclip |
|---|---|
| ❌ You have 20 Claude Code tabs open and can't track which one does what. On reboot you lose everything. | ✅ Tasks are ticket-based, conversations are threaded, sessions persist across reboots. |
| ❌ You manually gather context from several places to remind your bot what you're actually doing. | ✅ Context flows from the task up through the project and company goals — your agent always knows what to do and why. |
| ❌ Folders of agent configs are disorganized and you're re-inventing task management, communication, and coordination between agents. | ✅ Paperclip gives you org charts, ticketing, delegation, and governance out of the box — so you run a company, not a pile of scripts. |
| ❌ Runaway loops waste hundreds of dollars of tokens and max your quota before you even know what happened. | ✅ Cost tracking surfaces token budgets and throttles agents when they're out. Management prioritizes with budgets. |
| ❌ You have recurring jobs (customer support, social, reports) and have to remember to manually kick them off. | ✅ Heartbeats handle regular work on a schedule. Management supervises. |
| ❌ You have an idea, you have to find your repo, fire up Claude Code, keep a tab open, and babysit it. | ✅ Add a task in Paperclip. Your coding agent works on it until it's done. Management reviews their work. |
Why Paperclip is special
Paperclip handles the hard orchestration details correctly.
| Atomic execution. | Task checkout and budget enforcement are atomic, so no double-work and no runaway spend. |
| Persistent agent state. | Agents resume the same task context across heartbeats instead of restarting from scratch. |
| Runtime skill injection. | Agents can learn Paperclip workflows and project context at runtime, without retraining. |
| Governance with rollback. | Approval gates are enforced, config changes are revisioned, and bad changes can be rolled back safely. |
| Goal-aware execution. | Tasks carry full goal ancestry so agents consistently see the "why," not just a title. |
| Portable company templates. | Export/import orgs, agents, and skills with secret scrubbing and collision handling. |
| True multi-company isolation. | Every entity is company-scoped, so one deployment can run many companies with separate data and audit trails. |
What's Under the Hood
Paperclip is a full control plane, not a wrapper. Before you build any of this yourself, know that it already exists:
┌──────────────────────────────────────────────────────────────┐
│ PAPERCLIP SERVER │
│ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │Identity & │ │ Work & │ │ Heartbeat │ │Governance │ │
│ │ Access │ │ Tasks │ │ Execution │ │& Approvals│ │
│ └───────────┘ └───────────┘ └───────────┘ └───────────┘ │
│ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │ Org Chart │ │Workspaces │ │ Plugins │ │ Budget │ │
│ │ & Agents │ │ & Runtime │ │ │ │ & Costs │ │
│ └───────────┘ └───────────┘ └───────────┘ └───────────┘ │
│ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │ Routines │ │ Secrets & │ │ Activity │ │ Company │ │
│ │& Schedules│ │ Storage │ │ & Events │ │Portability│ │
│ └───────────┘ └───────────┘ └───────────┘ └───────────┘ │
└──────────────────────────────────────────────────────────────┘
▲ ▲ ▲ ▲
┌─────┴─────┐ ┌─────┴─────┐ ┌─────┴─────┐ ┌─────┴─────┐
│ Claude │ │ Codex │ │ CLI │ │ HTTP/web │
│ Code │ │ │ │ agents │ │ bots │
└───────────┘ └───────────┘ └───────────┘ └───────────┘
The Systems
|
Identity & Access — Two deployment modes (trusted local or authenticated), board users, agent API keys, short-lived run JWTs, company memberships, invite flows, and OpenClaw onboarding. Every mutating request is traced to an actor. |
Org Chart & Agents — Agents have roles, titles, reporting lines, permissions, and budgets. Adapter examples match the diagram: Claude Code, Codex, CLI agents such as Cursor/Gemini/bash, HTTP/webhook bots such as OpenClaw, and external adapter plugins. If it can receive a heartbeat, it's hired. |
|
Work & Task System — Issues carry company/project/goal/parent links, atomic checkout with execution locks, first-class blocker dependencies, comments, documents, attachments, work products, labels, and inbox state. No double-work, no lost context. |
Heartbeat Execution — DB-backed wakeup queue with coalescing, budget checks, workspace resolution, secret injection, skill loading, and adapter invocation. Runs produce structured logs, cost events, session state, and audit trails. Recovery handles orphaned runs automatically. |
|
Workspaces & Runtime — Project workspaces, isolated execution workspaces (git worktrees, operator branches), and runtime services (dev servers, preview URLs). Agents work in the right directory with the right context every time. |
Governance & Approvals — Board approval workflows, execution policies with review/approval stages, decision tracking, budget hard-stops, agent pause/resume/terminate, and full audit logging. Nothing ships without your sign-off. |
|
Budget & Cost Control — Token and cost tracking by company, agent, project, goal, issue, provider, and model. Scoped budget policies with warning thresholds and hard stops. Overspend pauses agents and cancels queued work automatically. |
Routines & Schedules — Recurring tasks with cron, webhook, and API triggers. Concurrency and catch-up policies. Each routine execution creates a tracked issue and wakes the assigned agent — no manual kick-offs needed. |
|
Plugins — Instance-wide plugin system with out-of-process workers, capability-gated host services, job scheduling, tool exposure, and UI contributions. Extend Paperclip without forking it. |
Secrets & Storage — Instance and company secrets, encrypted local storage, provider-backed object storage, attachments, and work products. Sensitive values stay out of prompts unless a scoped run explicitly needs them. |
|
Activity & Events — Mutating actions, heartbeat state changes, cost events, approvals, comments, and work products are recorded as durable activity so operators can audit what happened and why. |
Company Portability — Export and import entire organizations — agents, skills, projects, routines, and issues — with secret scrubbing and collision handling. One deployment, many companies, complete data isolation. |
What Paperclip is not
| Not a chatbot. | Agents have jobs, not chat windows. |
| Not an agent framework. | We don't tell you how to build agents. We tell you how to run a company made of them. |
| Not a workflow builder. | No drag-and-drop pipelines. Paperclip models companies — with org charts, goals, budgets, and governance. |
| Not a prompt manager. | Agents bring their own prompts, models, and runtimes. Paperclip manages the organization they work in. |
| Not a single-agent tool. | This is for teams. If you have one agent, you probably don't need Paperclip. If you have twenty — you definitely do. |
| Not a code review tool. | Paperclip orchestrates work, not pull requests. Bring your own review process. |
Quickstart
Open source. Self-hosted. No Paperclip account required.
npx paperclipai onboard --yes
Troubleshooting: private npm registry
.npmrcIf this fails with an
E404forpaperclipai(or similar) and you use a private npm registry (for example GitHub Packages) via a global~/.npmrc,npxmay be resolvingpaperclipaiagainst that private registry instead of the public npm registry.Diagnostic:
npm config get registryWorkaround (cross-platform; force the public npm registry for this command):
npx --registry https://registry.npmjs.org paperclipai onboard --yes
That quickstart path now defaults to trusted local loopback mode for the fastest first run. To start in authenticated/private mode instead, choose a bind preset explicitly:
npx paperclipai onboard --yes --bind lan
# or:
npx paperclipai onboard --yes --bind tailnet
If you already have Paperclip configured, rerunning onboard keeps the existing config in place. Use paperclipai configure to edit settings.
Or manually:
git clone https://github.com/paperclipai/paperclip.git
cd paperclip
pnpm install
pnpm dev
This starts the API server at http://localhost:3100. An embedded PostgreSQL database is created automatically — no setup required.
Requirements: Node.js 20+, pnpm 9.15+
FAQ
What does a typical setup look like? Locally, a single Node.js process manages an embedded Postgres and local file storage. For production, point it at your own Postgres and deploy however you like. Configure projects, agents, and goals — the agents take care of the rest.
If you're a solo entrepreneur you can use Tailscale to access Paperclip on the go. Then later you can deploy to e.g. Vercel when you need it.
Can I run multiple companies? Yes. A single deployment can run an unlimited number of companies with complete data isolation.
How is Paperclip different from agents like OpenClaw or Claude Code? Paperclip uses those agents. It orchestrates them into a company — with org charts, budgets, goals, governance, and accountability.
Why should I use Paperclip instead of just pointing my OpenClaw to Asana or Trello? Agent orchestration has subtleties in how you coordinate who has work checked out, how to maintain sessions, monitoring costs, establishing governance - Paperclip does this for you.
(Bring-your-own-ticket-system is on the Roadmap)
Do agents run continuously? By default, agents run on scheduled heartbeats and event-based triggers (task assignment, @-mentions). You can also hook in continuous agents like OpenClaw. You bring your agent and Paperclip coordinates.
Development
pnpm dev # Full dev (API + UI, watch mode)
pnpm dev:once # Full dev without file watching
pnpm dev:server # Server only
pnpm build # Build all
pnpm typecheck # Type checking
pnpm test # Cheap default test run (Vitest only)
pnpm test:watch # Vitest watch mode
pnpm test:e2e # Playwright browser suite
pnpm db:generate # Generate DB migration
pnpm db:migrate # Apply migrations
pnpm test does not run Playwright. Browser suites stay separate and are typically run only when working on those flows or in CI.
See doc/DEVELOPING.md for the full development guide.
Roadmap
- ✅ Plugin system (e.g. add a knowledge base, custom tracing, queues, etc)
- ✅ Get OpenClaw / claw-style agent employees
- ✅ companies.sh - import and export entire organizations
- ✅ Easy AGENTS.md configurations
- ✅ Skills Manager
- ✅ Scheduled Routines
- ✅ Better Budgeting
- ✅ Agent Reviews and Approvals
- ✅ Multiple Human Users
- ⚪ Cloud / Sandbox agents (e.g. Cursor / e2b / Novita agents)
- ⚪ Artifacts & Work Products
- ⚪ Memory / Knowledge
- ⚪ Enforced Outcomes
- ⚪ MAXIMIZER MODE
- ⚪ Deep Planning
- ⚪ Work Queues
- ⚪ Self-Organization
- ⚪ Automatic Organizational Learning
- ⚪ CEO Chat
- ⚪ Cloud deployments
- ⚪ Desktop App
This is the short roadmap preview. See the full roadmap in ROADMAP.md.
Community & Plugins
Find Plugins and more at awesome-paperclip
Observability
Paperclip ships with opt-in OpenTelemetry auto-instrumentation for the server (traces only). It activates when OTEL_EXPORTER_OTLP_ENDPOINT is set and supports grpc, http/protobuf, and http/json via the standard OTEL_EXPORTER_OTLP_PROTOCOL env var. The @opentelemetry/* packages are optional peer dependencies — install them only if you want tracing. See doc/observability.md for install commands and the full env-var reference.
Telemetry
Paperclip collects anonymous usage telemetry to help us understand how the product is used and improve it. No personal information, issue content, prompts, file paths, or secrets are ever collected. Private repository references are hashed with a per-install salt before being sent.
Contributors changing emitted telemetry events should follow the Telemetry Data Contract. For proposed first-party events that are not in the generated contract yet, follow Telemetry Workflow.
Telemetry is enabled by default and can be disabled with any of the following:
| Method | How |
|---|---|
| Environment variable | PAPERCLIP_TELEMETRY_DISABLED=1 |
| Standard convention | DO_NOT_TRACK=1 |
| CI environments | Automatically disabled when CI=true |
| Config file | Set telemetry.enabled: false in your Paperclip config |
Contributing
We welcome contributions. See the contributing guide for details.
Community
- Discord — Join the community
- Twitter / X — Follow updates and announcements
- GitHub Issues — bugs and feature requests
- GitHub Discussions — ideas and RFC
License
MIT © 2026 Paperclip Labs, Inc
Star History
Open source under MIT. Built for people who want to get work done, not babysit agents.
