## Thinking Path > - Paperclip is the open source app people use to manage AI agents for work > - A task on a remote (Daytona) sandbox continues from its saved workspace. Before the agent starts, the server uploads the saved archive into the sandbox and a sandbox script extracts it. > - The extraction wrote a full second copy of the workspace beside the uploaded archive. A 7.5 GB workspace on a fresh sandbox then needed about 15 GB, and the restore failed with `stage=extract code=ENOSPC disk=full`. > - The failure was classified as retryable, so every automatic retry and every Retry repeated it on a same-size sandbox. The task could not continue. > - On a retained sandbox it is worse: the old root, the archive, and the new tree all share the disk. > - This pull request makes the restore need about one copy of the workspace. The sandbox removes only data that control-plane storage already holds durably, and it never removes a root whose save the server did not prove. > - The benefit is that a workspace that fits once on the sandbox disk restores. A disk that is too small for one copy now gets a named failure that does not loop. ## Linked Issues or Issue Description **What happened?** A saved remote workspace of about 7.5 GB could not be restored on a new Daytona sandbox. The run failed with `remote_workspace_restore_failed: step=sandbox_restore; remote_workspace_operation_failed: operation=restore exit=1; remote_workspace_restore_failed: stage=extract code=ENOSPC disk=full exit=1`. The run marked the failure as retryable, and each retry failed the same way. **Steps to reproduce** 1. Save a remote workspace whose archive is larger than half of the free sandbox disk. 2. Start the next run on another sandbox, so that the server restores the saved archive. 3. The upload succeeds. The extraction writes the second copy and fails with ENOSPC. **Expected behavior** A workspace that fits once on the sandbox disk restores. A disk that cannot hold one copy gives a specific failure that is not retried automatically, and Retry works after the sandbox has more space. **What the disk holds during a restore (from the code)** - The uploaded archive (`<parent>/.paperclip-runtime/workspace-snapshots/<operation>/workspace.pcws`, about the workspace size, because the archive is not compressed). - The extracted tree (`<root>.restoring-*`, the workspace size). - On a retained sandbox only: the old root, which stayed until after the new root was published. - After a restore that died: its partial tree and its archive, which no later attempt removed. Refs #20678 (the save side of the same full-disk class). ## What Changed - `workspaceArchive` restore has a `consumeArchive` mode. It creates the directories and symlinks first, then writes the file bodies from the last to the first. After it verifies each file against the manifest hash, it truncates the archive behind that file. The archive and the tree together need the workspace size plus the largest file. The default mode, which the server uses for local restores, does not change. - The sandbox restore script uses that mode on a private rename of the uploaded archive. A later upload to the same path cannot change the file that is being consumed. The script removes the consumed file when it stops. - The helper's own staging is now inside the root-specific `<root>.restoring-*` folder, not in a shared `.workspace-restore-*` sibling. - While it holds the root's restore lock, and after the epoch fence, the script removes leftovers of an earlier attempt on the same root that died: `<root>.restoring-*` folders, `.consuming` archives in its own staging, and archive staging folders that a `restore-target.json` binds to the same root. Each restore writes that binding after the reclaim step. - When the server proved that a retained root is its own earlier, fully saved allocation (`replaceRetiredRoot` and a Paperclip receipt, as before), the script removes the root's files before the extraction, not after the publish. The receipt and `.paperclip-runtime` stay, so an interrupted restore proves the same root again and continues. - A full disk at any restore stage reports `reason=sandbox_disk_full`. The existing named-refusal rule makes it non-retryable, so it goes to the board recovery action and does not loop. - `doc/execution-semantics.md` describes the disk need, the reclaim, the early removal, and the new reason. ## Verification - `cd server && npx vitest run src/services/remote-workspace-transport.test.ts src/services/remote-workspace-snapshot-archive.test.ts` (287 passed). - `cd server && npx vitest run src/services/remote-workspaces.integration.test.ts src/services/remote-workspace-lifecycle.test.ts src/services/remote-workspace-archive-worker.test.ts src/services/remote-workspace-snapshot-archive-environments.test.ts` (122 passed, 16 skipped). - `cd server && npx tsc --noEmit -p tsconfig.json` (pass). - The new tests run the real sandbox scripts against a folder with a byte capacity. A `--require` preload makes each file write fail with ENOSPC when the folder would exceed the capacity. - Red on `origin/master`, green with this change: - Fresh sandbox, room for the archive plus one file: master fails with the exact production error `stage=extract code=ENOSPC disk=full exit=1`. The fix restores every byte and leaves only the restored files. - Retained root that the server proved, room for the old root, the archive, and one file: master fails with ENOSPC. The fix restores and keeps the runner state. - Too small for one copy: the failure is `stage=extract reason=sandbox_disk_full`, with no partial tree or archive left. A retry with more space then restores. - Both sandbox processes are killed mid-extraction (a restart): a retry with the same identity and a retry with a new identity and epoch both reclaim the leftovers and restore into the same capacity. - The command dies right after it removed a proven root's files: the next restore proves the root again from its kept receipt, restores, and keeps the runner state. - Integration test through `prepareRemoteWorkspace`: a full disk gives `retryable: false` with `reason=sandbox_disk_full`. On master the same case is `retryable: true`. - Guards (pass on master and with the fix): a retained root without the server proof, or without a Paperclip receipt, is refused with `reason=occupied_root`, and none of its files are removed. - Previous-release story: the archive format and the saved state do not change. A partial `<root>.restoring-*` tree from the previous release is reclaimed (test). Archive staging from the previous release has no binding, so it is kept (test). The previous release's shared `.workspace-restore-*` siblings cannot be bound to a root, so they are kept. ## Risks - The consumed archive cannot be read again. Each restore uploads a new copy from control-plane storage, and the early-return path for an already restored root does not read the archive. Every file is still checked against the manifest, and the manifest is checked against the saved digest. - The reclaim step removes data only under the root's restore lock and after the epoch fence. It removes only names that a restore of the same root creates. Staging that names another root, or no root, is kept. - The early removal of a retained root depends on the existing server proof (`isRetiredOwnAllocation`) and the receipt check. If a restore fails after the removal, the saved version in storage is the source of truth, and the next restore proves the same root again. - Files in a lower overlay layer of a resumed sandbox image do not free space when they are removed. Such a sandbox can still be full. - A workspace that is larger than the free disk after the upload, plus its largest file, still fails. It now fails with the named, non-retryable `reason=sandbox_disk_full`. - No change to `packages/paperclip-runner`, the database schema, or the API. ## Model Used - Anthropic Claude Opus 5.5 (`claude-opus-5-5`), used through Claude Code with tool use (shell, file edits, test runs). ## 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 - [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 <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
Star History
Open source under MIT. Built for people who want to get work done, not babysit agents.
