Agentdesktop discovers AI developer tools, inventories MCP servers and skills, applies tool-native configuration and sandbox policy, and connects each device to an LLM gateway with user and device identity.
Keep developers in Claude Code, Codex, Cursor, OpenCode, VS Code, and Grok Build while giving platform teams one place to understand and manage the fleet.
Website · Documentation · Announcement · Releases
Why Agentdesktop?
AI agents increasingly run on employee workstations, but the controls around them are fragmented across tool-specific settings, MCP connections, skills, provider credentials, and local configuration files.
MDM remains the right layer for enrolling devices, deploying software, and enforcing OS posture. Agentdesktop adds the AI-tool-aware layer above it.
| See what is running | Manage tools natively | Control model access |
|---|---|---|
| Discover supported tools and versions, then inventory MCP servers, skills, and models without collecting their secrets or contents. | Define configuration and sandbox intent once. Agentdesktop translates it into each supported tool's native format and reports whether it was applied. | Route tools through your LLM gateway with short-lived credentials carrying user, device, and allowed client context. Provider API keys remain at the gateway. |
Start on one workstation
Try the same endpoint daemon used in a managed fleet without deploying a controller.
1. Install Agentdesktop
Download the current device binary from GitHub Releases, or build it from source:
git clone https://github.com/agentdesktop-dev/agentdesktop.git cd agentdesktop corepack enable make install
2. Preview the standalone example
The repository includes a working standalone configuration for Claude Code, OIDC, and Agentgateway. Preview every proposed file action without changing tool configuration:
agentdesktop daemon \ --config examples/standalone/config.yaml \ --user \ --dry-run
3. Run and inspect
Remove --dry-run to reconcile the configuration and leave the daemon
running:
export ANTHROPIC_API_KEY=sk-ant-...
docker compose -f examples/standalone/compose.yaml up -d
agentdesktop daemon \
--config examples/standalone/config.yaml \
--userIn another terminal, check the daemon and list discovered tools and models:
agentdesktop status agentdesktop discover
The desktop and fleet interfaces also expose the MCP server and skill inventory. See the standalone quickstart for prerequisites, test credentials, and a walkthrough of the local services.
Start locally, grow into a fleet
Agentdesktop uses the same daemon and tool-native configuration model at every stage.
| Standalone | Controller-managed |
|---|---|
| Read policy from local YAML, discover and configure tools on one workstation, and authenticate the user directly to a compatible LLM gateway. No controller or device identity is required. | Centrally inventory a fleet, distribute versioned configuration, enroll users and devices, report reconciliation status, and issue short-lived gateway credentials. |
| Run the standalone quickstart | Run the managed quickstart |
Core capabilities
- AI tool discovery: detect supported developer tools and their versions across Linux, macOS, and Windows.
- Secret-minimizing inventory: report configured MCP servers and skills without collecting MCP command arguments, environment variables, HTTP headers, or skill bodies.
- Tool-native configuration: safely merge managed values into the formats expected by each tool while preserving unrelated user settings.
- Shared sandbox policy: translate filesystem and network restrictions into the native sandbox configuration supported by Claude Code and Codex.
- User and device identity: bind a locally generated device key and certificate to the user who enrolled the workstation through OIDC.
- Runtime credentials: give supported tools short-lived credentials instead of distributing long-lived provider keys to workstations.
- Identity-aware gateway integration: attach user, device, and allowed client context for gateway routing, policy, logging, and usage attribution.
- Opt-in telemetry: collect selected session and tool-use events when an organization enables them.
Supported tools
| Tool | Discovery | Managed configuration | MCP and skills inventory | Sandbox policy |
|---|---|---|---|---|
| Claude Code | Yes | Yes | MCP and skills | Yes |
| Claude Desktop | Yes | Yes | MCP | — |
| Codex | Yes | Yes | MCP and skills | Yes |
| Cursor | Yes | — | MCP and skills | — |
| OpenCode | Yes | Yes | MCP | — |
| VS Code | Yes | — | MCP and skills | — |
| Grok Build | Yes | System mode | MCP and skills | — |
Don't see your tool? We're actively expanding this list and would love your help. Open an integration request to tell us what you use, or contribute discovery and configuration support for another AI developer tool or harness.
The project targets Linux, macOS, and Windows. Support varies where a tool or operating system does not expose an equivalent native configuration surface.
How it works
The daemon runs on each workstation and reconciles developer-tool configuration. It can receive desired configuration from the controller or read the same YAML directly in standalone mode. Managed tools continue to run locally and can request credentials for an LLM gateway through the daemon.
In controller-managed mode, the daemon generates its private device key on the workstation and sends only a certificate signing request to the controller. After enrollment, protected controller operations require the device certificate and a valid token for the user who enrolled it.
When a supported tool requests gateway access, the controller can issue a short-lived JWT containing the user, device ID, allowed client label, audience, issuer, and expiry. The client label is asserted by the local helper; it is useful for policy and attribution, but it is not cryptographic proof of the calling executable.
Read the announcement for a deeper walkthrough of standalone mode, enrollment, and short-lived tool credentials.
Project and community
Agentdesktop is fully open source under the Apache License 2.0.
- Read the documentation.
- Browse or report issues.
- Help us add support for another AI developer tool.
- Review the Code of Conduct before contributing.
- See the production guide for Kubernetes, certificates, MDM, and endpoint enrollment.