## Thinking Path > - Paperclip is the open source app people use to manage AI agents for work > - Native OpenCode, Codex and Cursor Cloud chat turns run through runnerd. runnerd reads provider frames in order and keeps the run's provider state in a durable file > - For every frame that it reads, runnerd rewrote the whole provider state file and called `fsync` on the file and on its directory. The state holds every tool result kept in the turn, so each save got more expensive as the turn went on > - A tool call request is just the next frame. It waited behind one full save for every frame before it. #20209 measured tool-call turnaround that grew from about 1.4 s to about 15 s in one turn > - #20209 stopped the OpenCode proxy from sending frames that runnerd discards. Every frame that runnerd still reads still paid a full save, and other proxies (for example Cursor Cloud) still send such frames > - This pull request makes runnerd save the frames of one poll once, before anything derived from them leaves runnerd. A save that would write the bytes already on disk is skipped > - The benefit is that the number of saves before a tool call no longer grows with the number of streamed frames. In a local measurement, a tool call after 400 frames with 830 KB of kept state took 0.57 s instead of more than 30 s ## Linked Issues or Issue Description Refs #20209 Related: #17514 (the same per-event full-state rewrite, on the server control-plane side) **What happened** During a native OpenCode chat turn, tool-call turnaround grew from about 1.4 s to about 15 s as the turn went on. runnerd saved its complete durable provider state, with `fsync`, after every provider frame. That state includes the tool results kept so far in the turn. A tool call request waited behind one full save for each earlier frame. **Expected behavior** The time to deliver a tool call must not grow with the number of assistant-text, reasoning or item frames that came before it. A crash or restart must still never lose state that a resumed run needs. **Steps to reproduce** 1. Start a native OpenCode (or Codex app-server or Cursor Cloud) turn that keeps a few tool results and then streams many text or reasoning frames before its next tool call. 2. Measure the time from the tool call frame to the `semantic_tool.input` event. 3. See that the time grows with the number of earlier frames and with the size of the kept state. Locally, `cargo test -p paperclip-runner-core --lib measure_streamed_frame -- --ignored --nocapture` on `master` reports 102 saves and 9.3 s for 100 frames with 830 KB of kept state, and more than 30 s for 400 frames. ## What Changed - `packages/paperclip-runner/runner/crates/runner-core/src/provider_backend.rs` and `codex_provider.rs`: - The provider frame loop moves into `poll_provider_frames`. An ordinary notification frame and a descendant notification frame no longer save the state. They mark it as unsaved. - After the loop, `poll_current_provider_with_control` saves the unsaved state once. It also saves when a frame fails, before it returns the error. - Frames that already saved at once still do so: turn terminals, Cursor Cloud terminal deliveries, `reconciliation_required`, protocol failures, MCP permission and runtime requests, process exit, and new tool calls. - A tool call that runnerd answers at once (an exact completed replay or the receipt-limit stop) saves unsaved state before it writes to the provider. A rejected tool call already saved first. - `retained_events`, `execute` and `host_park_ready` save unsaved state first, so no event, command result or park decision can expose state that is not on disk. - Courtesy rejections that `CodexProvider::poll` writes by itself (unsupported requests, descendant requests, delayed requests after a terminal, full runtime-request capacity) are held while runnerd reads a batch (`hold_courtesy_responses`). runnerd sends them only after it saves the state that covers every earlier frame (`save_before_provider_writes`). A terminal frame also saves and releases them before runnerd asks the provider for goal state or drains the accounting tail. Released courtesy replies are best-effort, as courtesy replies were before: a provider that already closed stdin cannot turn a received terminal into a polling failure. The receipt-limit stop sends held cancellations before its `turn/interrupt` request, so their order to the provider does not change. - The trace records for runnerd's normalization (`rust_durable_normalization`), which name emitted event ids, are kept until the state that holds those ids is saved. The trace therefore only names saved events. Saved mappings are written before an exited or failed provider is dropped, so they are not lost. Raw frame records still go to the trace when a frame is read; they name no event ids. - `save_unsaved_frame_state` does not write when the serialized state is byte-for-byte the same as the saved file. All other saves write as before. - Serialization moves to `serialize_provider_state`, and the file write moves to `write_state_bytes`. The write path (private temporary file, `fsync`, rename, directory `fsync`, `0600`) does not change. - New tests in `packages/paperclip-runner/runner/crates/runner-core/src/tests/provider_frame_save_batching.rs`: - `streamed_frames_do_not_multiply_durable_saves_before_a_tool_call`: 8 and 48 streamed frame pairs before a tool call need the same number of saves (1). On `master` they need 18 and 98. - `batched_frame_state_is_saved_before_events_leave_and_survives_a_restart`: at every poll, the saved file is equal to the in-memory state and holds exactly the delivered events. A new executor loads the file after the old one stops and gets the same state, the same unacknowledged events and the pending tool call. - `batched_frame_state_is_saved_when_a_later_frame_fails`: a frame that fails after 20 batched frames still leaves those 20 frames on disk. - `previous_release_state_is_rewritten_by_the_first_batched_save`: a state file in an older shape (compact JSON without newer default fields) loads, and the first batched save rewrites it. Unchanged state is not rewritten. Changed state is. - `courtesy_rejections_reach_the_provider_only_after_earlier_frames_are_saved`: when the courtesy rejection reaches the provider, the saved file (what a restarted runnerd would load) already holds the 20 earlier frames and equals the in-memory state. It fails if the hold is removed. - `trace_interpretations_name_only_saved_events`: every event id that a trace record names is in saved state at the moment the record is written. It fails if records are written before the save. - `a_crash_inside_an_unsaved_batch_leaves_saved_state_and_provider_output_unchanged`: after 122 frames are read and not yet saved, the saved file is byte-for-byte unchanged and runnerd has written nothing to the provider. A reload gets the pre-batch event sequence and no pending events. - `a_held_cancellation_that_cannot_reach_the_provider_keeps_the_completed_turn`: the provider closes stdin and then completes the turn with a tool call still pending. The held cancellation cannot be written, and the turn still completes and is saved. - `trace_interpretations_survive_a_provider_exit_in_the_same_poll`: the trace keeps the mappings for frames that arrived in the same poll as the provider exit. - `measure_streamed_frame_cost_before_a_tool_call` (ignored): prints saves and tool-call latency for different frame counts and kept-state sizes. ## Verification - `cargo test --locked -p paperclip-runner-core` (debug, macOS arm64): library 595 passed, 1 failed; all 35 integration test binaries passed (`--no-fail-fast`). The one library failure is `task_memory::tests::monitor_bounds_notices`. It also fails when run alone, takes about 9 minutes, and waits on file-watch timing in `task_memory.rs`, which this PR does not touch. In one earlier run, two ACPX park tests in `acpx_park_preparation` failed. The same binary also failed on unchanged `master` (with a different test), and it passed in the final run. - `cargo test -p paperclip-runner-core --lib measure_streamed_frame -- --ignored --nocapture`, debug build, macOS APFS (`sync_all` is `F_FULLFSYNC`). Each row is one turn: frames streamed, then one tool call. | Kept state | Frames | Saves (master) | Tool-call latency (master) | Saves (this PR) | Tool-call latency (this PR) | | --- | --- | --- | --- | --- | --- | | 4 KB | 100 | 102 | 946 ms | 1 | 18 ms | | 4 KB | 400 | 405 | 3,791 ms | 7 | 70 ms | | 211 KB | 100 | 102 | 3,207 ms | 1 | 37 ms | | 211 KB | 400 | 405 | 12,803 ms | 7 | 193 ms | | 833 KB | 100 | 102 | 9,251 ms | 1 | 93 ms | | 833 KB | 400 | about 405 | more than 30 s (test deadline) | 7 | 567 ms | With 400 frames, the remaining saves are one per poll of up to 128 frames and one per controller acknowledgement. - With the debug `paperclip-runnerd` and `fake-codex-app-server` binaries from this branch: `npx vitest run` on `src/live/runnerd-opencode-streaming-tools`, `runnerd-opencode-assigned-tools`, `runnerd-codex-transport`, `runnerd-codex-transport-settlement`, `runnerd-codex-transport-cold-restore`, `runnerd-restart-continuation`, `runnerd-saved-continuation`, `runnerd-detach-durability`, and `src/cli/opencode-proxy-output`, `opencode-proxy-events`, `opencode-app-server-proxy`: 11 files, 353 tests passed. ## Risks - Durability. The rule is: nothing derived from a frame leaves runnerd before the state that holds that frame is on disk. That covers delivered events, command results, park decisions, tool results and rejections, courtesy rejections, Cursor Cloud terminal acknowledgements, and trace records that name event ids. The tests above check each of these. - The unsaved window is at most one poll (128 frames). Every frame in it is undelivered: no event from it reached the controller, and runnerd wrote nothing to the provider while it was unsaved. `a_crash_inside_an_unsaved_batch_leaves_saved_state_and_provider_output_unchanged` proves this. A crash in the window therefore leaves the saved state and everything the controller and provider have seen exactly as a crash just before those frames were read. The resumed run starts from the same event sequence, so it cannot deliver an event id twice. Its normal recovery (thread resume and `thread/read` reconciliation) handles those frames in the same way as frames still in the provider pipe. On `master`, a crash could already lose the one frame being processed. - One provider write can still happen in the window: `thread/read`, which `CodexProvider::poll` sends to check the lineage of an unknown helper thread. It is a read-only query that waits for its answer, and it changes nothing on the provider side. - Courtesy rejections now reach the provider at the end of the poll instead of during it. The delay is one batch. The provider gets the same replies. - Previous-release story: the saved file shape does not change, and no new field is saved. A file from the previous release loads as before. The skip check compares exact bytes, so an older file is never treated as already saved. The first save after an upgrade rewrites it in the current shape. A deploy that lands mid-turn sees a file that the previous release saved after each frame. That file is valid input for this code. - The ACPX backend has its own frame loop and is not changed here. ## Model Used - Anthropic Claude Opus 5.5 (`claude-opus-5-5`), used through Claude Code with tool use (shell, file editing) and extended thinking. ## 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 - [x] I have searched GitHub for duplicate or related PRs and linked them above - [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 updated relevant documentation to reflect my changes - [x] I have considered and documented any risks above - [ ] All Paperclip CI gates are green - [ ] 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 5.5 <noreply@anthropic.com>
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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. Choose models and harnesses per agent while keeping your team's tasks, skills, permissions, and history in one place.
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. |
| Works with |
OpenClaw |
Claude Code |
Codex |
Cursor + Cloud |
Gemini CLI |
OpenCode |
Pi |
Hermes + Gateway |
Grok Build |
Kimi Code |
If it can receive a heartbeat, it's hired.
Custom processes, HTTP endpoints, and external adapter packages extend the roster. See the adapter overview for setup and capabilities.
Paperclip is right for you if
- ✅ You want to build autonomous AI organizations
- ✅ 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
The four pillars
Four things have to work for an organization of AI agents to actually produce: the tasks, the org, the training, and the infrastructure. Paperclip is built around exactly those four pillars.
| Pillar | Built for | What it covers |
|---|---|---|
| Agentic Task Manager — Declare intent. Agents work. You verify the output. | Everyone, daily | Tasks, approvals & review gates · proactive agent coworkers · auditable routines & workflows · verify from diffs, screenshots & tests |
| Org Chart for Agents — Roles, permissions & boundaries for humans and agents. | Managers | Mixed human + agent org chart · responsibilities, delegation, specialization · governance: who can do what · scoped secrets & company boundaries · connection permissions & responsible-user identities |
| Agent Employee Training — Design, train & evaluate your AI employees. | Enablers | Skill Studio & shared org-wide skills · evals & saved test runs · active learning loops & quality metrics · performance reviews for agents · saved test inputs · skill version history & restore · reusable team templates |
| Agentic OS — The infrastructure that makes the work run. | IT & platform | Cross-provider runtime: any model, any agent · sandboxing, integrations & MCP servers · SSO, GRC, RBAC & cost controls · data privacy, internal trace collection, compounding data value · personal & shared app connections · run history & opt-in tracing |
Features
🔌 Bring Your Own AgentAny agent, any runtime, one org chart. If it can receive a heartbeat, it's hired. |
🎯 Goal AlignmentLink tasks and projects to your organization goals. Agents receive the goal context behind their work. |
💓 HeartbeatsAgents wake for assigned work, follow-up messages, or configured schedules. Delegation flows up and down the org chart. |
💰 Cost ControlCompany, agent, and project budgets. Track reported spend, get threshold alerts, and pause work at configured limits. |
🏢 Multi-OrganizationOne deployment, many organizations. Separate tasks, agents, permissions, and activity histories for each. |
🎫 Task ThreadsKeep conversations, plans, blockers, files, and run history attached to the work. Assign tasks to agents or people. |
🛡️ GovernanceConfigure review and approval stages, approve hires, and pause, reassign, or stop work when needed. |
📊 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. |
🔗 Apps & ConnectionsConnect services such as GitHub, Notion, and Railway, or your own MCP server. Set gateway actions to Allowed, Ask first, or Off. |
👥 Shared Agents, Personal AccountsChoose who can use a connection and which agents can access it. Managed GitHub operations can use the account of the person directing the work. |
🧠 Skills & Skill StudioInstall or write shared skills, test them with saved inputs, inspect results, and restore earlier versions. |
📅 Scheduled RoutinesRun recurring work on a schedule or trigger it through an API or webhook. Each run has a task, an owner, and a history. |
📎 Artifacts & FeedbackFind the files and documents agents produce. Preview supported formats and leave comments on specific passages in documents. |
📦 Ready-Made TeamsPreview and install teams with roles, skills, projects, and routines. Choose their runtimes and make the setup your own. |
Experimental Agent Chat and chat/email connectors add conversations with agents in Paperclip and through configured services such as Slack, Discord, Telegram, and AgentMail. Enable the relevant instance settings to try them.
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. | ✅ Spend tracking, budget alerts, and automatic pauses help you control the cost of ongoing work. |
| ❌ You have recurring jobs (customer support, social, reports) and have to remember to manually kick them off. | ✅ Routines create assigned tasks on a schedule, with outputs and run history you can inspect. |
| ❌ 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 task checkout. | A single assignee and execution locks prevent competing runs from claiming the same task. |
| Persistent work context. | Tasks, comments, and documents stay in Paperclip. Supporting adapters resume saved sessions across runs. |
| 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. |
| Accountable connections. | Human access, agent eligibility, and gateway action permissions are separate controls. Approve a call once or save a revocable rule. |
| Goal-aware execution. | Linked tasks and projects carry goal ancestry so agents see the "why," not just a title. |
| Portable company templates. | Export/import orgs, agents, and skills with secret scrubbing and collision handling. |
| Organization boundaries. | Company-scoped access checks keep each organization's work, agents, and activity separate within one deployment. |
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), human roles and permissions, agent API keys, short-lived run JWTs, company memberships, and invite flows. Responsible-user attribution follows work through delegation and supported managed connections. |
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. Search across work, review document revisions, and leave anchored feedback. |
Heartbeat Execution — DB-backed wakeup queue with coalescing, budget checks, workspace resolution, secret injection, skill loading, and adapter invocation. Runs produce logs, usage records, and adapter-specific session state. Bounded recovery handles supported failures and surfaces cases that need human action. |
|
Workspaces & Runtime — Project repositories and workspaces, optional isolated execution workspaces (git worktrees, operator branches), and runtime services (dev servers, preview URLs). Sandbox providers extend execution beyond the local host; availability depends on the configured environment and adapter. |
Governance & Approvals — Board approval workflows, execution policies with review/approval stages, decision tracking, budget hard-stops, and agent pause/resume/terminate. Configured task reviews govern completion; connection action approvals govern calls through the tool gateway. |
|
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. Enforcement uses recorded spend; usage reporting and in-flight work can delay a stop. |
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 — Company secrets and per-person secret values, encrypted credential storage, local or S3-compatible file storage, attachments, and work products. Secret references supply credentials to authorized runs without copying values into ordinary agent configuration. |
|
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 — Preview, export, and import organization packages with agents, skills, and optional projects, routines, tasks, and attachments. Referenced secret values are omitted; review packages before sharing because plain environment values and local paths can remain. Packages share an operating setup; full-instance recovery uses backups. |
What Paperclip is not
| Not just a chatbot. | Conversations stay attached to tasks, plans, decisions, and outputs. Experimental Agent Chat can hand work off to assigned tasks. |
| 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 just a workflow builder. | Routines operate within an organization, with roles, goals, budgets, and governance. |
| Not a prompt manager. | Agents bring their own prompts, models, and runtimes. Paperclip manages the organization they work in. |
| Not limited to one agent. | Start with one agent and grow into a team with shared skills, delegation, and review. |
| Not only for code review. | Coding and PR review fit alongside research, operations, content, and other work. |
Quickstart
Open source. Self-hosted. No Paperclip account required. Follow the guided quickstart to set up your first agent.
Just ask your agent to install Paperclip
Share the installation guide with your agent.
Or install it yourself
With Node.js 24.11 or newer installed:
npx paperclipai@latest onboard --yes
The CLI runs from npm's cache; your instance configuration and data persist locally.
See the installation guide for managed installs, pinned versions, canary and git-ref installs, updates, rollback, service management, and uninstalling.
For an isolated manual test instance that is already initialized with a CEO
agent, use test-drive. It stays in the foreground, never installs a service
or creates a first task, and opens the browser only after setup succeeds:
ANTHROPIC_API_KEY=... npx paperclipai test-drive
OPENAI_API_KEY=... npx paperclipai test-drive --harness codex
OPENROUTER_API_KEY=... npx paperclipai test-drive \
--harness opencode \
--model openrouter/anthropic/claude-sonnet-4.5
Each run without --data-dir gets a unique, retained temporary directory; its
absolute path is printed at startup. Pass --data-dir to reuse one, or
--no-browser to leave the initialized instance unopened. When invoked from a
linked Git worktree, test-drive also enables task execution in that worktree.
See the test-drive guide for credential and
reuse behavior.
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@latest 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@latest onboard --yes --bind lan
# or:
npx paperclipai@latest onboard --yes --bind tailnet
If you already have Paperclip configured, rerunning onboard keeps the existing config in place. Use npx paperclipai configure to edit settings.
Or manually:
git clone https://github.com/paperclipai/paperclip.git
cd paperclip
pnpm install
pnpm dev
This starts the UI and API at http://localhost:3100. An embedded PostgreSQL database is created automatically — no setup required.
Requirements: Node.js 24.11+, pnpm 9.15+
Local Claude and Codex subscription sign-in also needs Python 3 and the corresponding provider CLI on the Paperclip host. The Docker image includes them.
Source development also builds the native Paperclip Runner when enabled (the self-hosted default). Install a Rust toolchain, or set PAPERCLIP_RUNNER_BINARY to a compatible prebuilt runner.
FAQ
Q: Is this project maintained or just slop?
A: Paperclip is maintained by the Paperclip team. We've merged over 2,700 pull requests.
Q: What does a typical setup look like?
A: 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.
For remote access, use authenticated mode with a private-network bind such as Tailscale, or deploy the persistent server with Docker. See deployment modes and the Docker guide.
Q: Can I run multiple companies?
A: Yes. A single deployment can host multiple organizations with company-scoped data and access checks.
Q: How is Paperclip different from agents like OpenClaw or Claude Code?
A: Paperclip uses those agents. It orchestrates them into a company — with org charts, budgets, goals, governance, and accountability.
Q: Why should I use Paperclip instead of just pointing my OpenClaw to Asana or Trello?
A: 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)
Q: Do agents run continuously?
A: Agents wake for assigned work and follow-up messages. Optional timer heartbeats let them check for work periodically; routines create recurring tasks on their own schedules. You can also connect externally running agents such as OpenClaw. A mention alone does not assign work or wake another agent.
Development
pnpm dev # Full dev (API + UI, watch mode)
pnpm dev:once # Full dev without file watching
pnpm dev:server # Server only
pnpm dev:mobile # Serve prebuilt UI on :3101 for phones/tablets (proxies /api → :3100)
pnpm dev:both # Run `pnpm dev` and `pnpm dev:mobile` together
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, Skill Studio & Skills Store
- ✅ Scheduled Routines
- ✅ Better Budgeting
- ✅ Agent Reviews and Approvals
- ✅ Multiple Human Users
- ✅ Cloud / Sandbox agents (e2b, Cloudflare, Daytona, Modal, Novita, boxd, self-hosted Kubernetes)
- ✅ Artifacts & Work Products
- ✅ Deep Planning (planning mode, revisioned plans, plan approvals)
- ✅ Enforced Outcomes (watchdogs, recovery actions, review gates)
- ✅ MCP Tool Gateway & Apps (governed tool access)
- ✅ Secrets Manager with per-agent access
- ✅ Activity log & action attribution
- ✅ Self-healing runs & automatic recovery
- ✅ Agent evals & feedback
- ✅ Connected Apps
- ✅ Personal & Shared AI Accounts
- ✅ Shared Agents Use Personal GitHub Identities
- ✅ Skill Version History & Restore
- ✅ Document Comments & Revision History
- ✅ Company-Wide Search
- ✅ Multi-Model & Multi-Harness Teams
- 🟡 Memory / Knowledge
- ⚪ MAXIMIZER MODE
- ⚪ Work Queues
- ⚪ Self-Organization
- ⚪ Automatic Organizational Learning
- 🟡 Agent Chat
- 🟡 Cloud deployments
- ⚪ Desktop App
- ⚪ Bring-your-own-ticket-system (Asana / Linear / Jira as on-ramps)
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. @opentelemetry/api is a normal server dependency; the SDK, auto-instrumentation, and exporter 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.
Paperclip also ships with opt-in Sentry error monitoring for the server and the browser. Set SENTRY_DSN_FRONTEND to activate it for the browser and SENTRY_DSN_BACKEND to activate it for the server — each variable is optional, and the legacy SENTRY_DSN variable still works as a fallback for either component. The supported server SDK version is @sentry/node@10.71.0; it is an optional peer dependency for the server, so install it only if you want error monitoring. The browser SDK, @sentry/browser, is pinned to the same exact version. See doc/observability.md for the install command, the privacy settings, and the full default capture set.
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
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Open source under MIT. Built for people who want to get work done, not babysit agents.
