withHuman withHuman

Approval layer for AI Agents
Put your most consequential agent actions behind human approvals, so your agents can do real work.

Latest release Release build Docker image Go version License: Elastic 2.0 Agent Approval Protocol Chat on Discord Follow @withHumanAI on X

Website · Docs · Quickstart · Protocol · Discord · Contributing

--- We want agents to do more than read data and suggest what to do next. They should be able to roll back a deployment, issue a refund, or merge code. Those actions have consequences, and teams need a way to bring a person in before they happen. withHuman is the approval layer for that moment. It checks an agent's tool call before it runs against rules you define in one place. Routine calls can be approved automatically, disallowed calls can be denied, and consequential ones can wait for the right person to decide. Every agent you connect follows those rules.

The review page for a pending issue_refund request: its arguments, the agent's explanation, and Deny and Approve buttons The review page for a pending issue_refund request: its arguments, the agent's explanation, and Deny and Approve buttons

## How it works An adapter (a runtime hook or an SDK wrapper) sends each tool call to withHuman before it runs, over the open [Agent Approval Protocol](https://agentapprovalprotocol.io). ```mermaid sequenceDiagram participant Agent as Your agent participant WH as withHuman participant You as You Agent->>WH: Wants to call issue_refund(amount: 75) WH->>WH: Checks your approval pipeline WH->>You: Asks for approval by email, Slack or Discord You->>WH: Approve WH->>Agent: Go ahead Agent->>Agent: Runs issue_refund ``` - **Approval pipelines** approve, deny or ask a person, based on the tool and its arguments. For example: approve refunds up to $20, ask payments above that. - **Escalation paths** choose who is asked and when, by team, level and working hours. Reviewers get email, Slack or Discord and decide in the web app with the exact arguments in front of them. See [How withHuman works](https://withhuman.ai/docs/concepts/how-withhuman-works) for how the pieces fit together. ## Quickstart You need [Docker](https://docs.docker.com/get-docker/). ```sh docker run -d --name withhuman -p 8080:8080 -v withhuman-data:/data quay.io/withhuman/bundle:latest docker exec withhuman cat /data/bootstrap-secret ``` Open [http://localhost:8080](http://localhost:8080), choose **First setup** and enter the secret. The welcome page connects your first agent and ends with a test call for you to approve. The [quickstart guide](https://withhuman.ai/docs/getting-started/quickstart) covers each step. To run from source instead, install Go (the version in [`go.mod`](go.mod)) and Node 25, then run `make frontend && go run ./cmd/withhuman`. The secret is in `~/.withhuman/bootstrap-secret`. ## Connect your agents - **Coding agents.** Claude Code, Codex, OpenClaw, Pi, Hermes and DeepSeek connect with the [`withhuman` CLI](deployment/cli/README.md): ```sh curl -fsSL https://downloads.withhuman.ai/install.sh | sh withhuman agent install --url https://approvals.example.com ``` - **Agents you build.** LangGraph, Pydantic AI, the OpenAI Agents SDK, CrewAI, Mastra and other frameworks connect through the [AAP SDKs](https://agentapprovalprotocol.io/docs/sdks/overview). See the [examples](examples/). ## Explore further - [Agents](https://withhuman.ai/docs/concepts/agents): agents and their instances. - [Approval pipelines](https://withhuman.ai/docs/concepts/approval-pipelines): how a request gets its decision. - [Escalation paths](https://withhuman.ai/docs/concepts/escalation-paths): who reviews a request and when. - [Requests and decisions](https://withhuman.ai/docs/concepts/requests-and-decisions): what the agent gets back. - [Review queue](https://withhuman.ai/docs/web-app/review-queue): where reviewers decide. ## Agent skills Teach your coding agent to connect runtimes and write approval pipelines: ```sh npx skills add https://withhuman.ai ``` The skills live in [`skills/`](skills/). ## Deploy Settings are environment variables, listed in [`.env.example`](.env.example). Before you go beyond your own machine: 1. Serve it behind HTTPS and set `WITHHUMAN_PUBLIC_ORIGIN` to that origin. 2. Set `WITHHUMAN_TRUSTED_PROXIES` to your proxy's addresses only. 3. Set `WITHHUMAN_SECRETS_KEY` and keep it safe. 4. Configure SMTP so invitations and password resets reach people. 5. Back up the whole data directory. 6. Set `OTEL_EXPORTER_OTLP_ENDPOINT` to collect its OpenTelemetry metrics. Don't want to run it yourself? [withhuman.ai](https://withhuman.ai) hosts it and adds the audit log, the AI judge, the MCP gateway, phone notifications and single sign-on. ## Telemetry Once a day withHuman sends a random installation ID, its version, the platform and whether it runs as a binary, a container or on Kubernetes. The answer tells administrators about new releases and security fixes on the **Version** settings page. Nothing about your organizations, people, agents or requests is sent. Set `WITHHUMAN_TELEMETRY=off` (or `DO_NOT_TRACK=1`) to turn it off. See [Updates and telemetry](https://withhuman.ai/docs/web-app/updates-and-telemetry). ## Community - **Questions and chat:** [Discord](https://discord.gg/3QWECnEvrk) - **Bugs and ideas:** [GitHub Issues](https://github.com/withHumanAI/withHuman/issues) - **Security vulnerabilities:** follow [SECURITY.md](SECURITY.md). Do not open an issue. - **Contributing:** [CONTRIBUTING.md](CONTRIBUTING.md) and the [code of conduct](CODE_OF_CONDUCT.md) - **Updates:** [@withHumanAI](https://x.com/withHumanAI) on X ## License withHuman is licensed under the [Elastic License 2.0](LICENSE).