en usage sandbox runtime relationships

Runtimes and Extensions

LangBot ships four extension mechanisms in parallel — plugins, MCP, Skills, and the sandbox — and they are easy to confuse. This page sorts out what each one does and when to use it.

One-line Summary

• Sandbox: an execution environment that lets the Agent run commands and read/write files
• Skills: on-demand instruction packages that hand the Agent a specialized workflow when needed
• MCP Server: connects to external tool services
• Plugin: a long-running extension process that can ship its own config page, event listeners, and knowledge components

Comparison

Capability	Provided by	How the Agent sees it	When to use
Sandbox	Box Runtime	The six tools exec/read/write/edit/glob/grep are attached directly	Agent needs to run code or read/write files
Skills	Box Runtime skill store	After the Agent calls activate, instructions are injected via Tool Result	Hand the Agent a workflow, template, or script, triggered on demand
MCP Server	LangBot MCP Loader (stdio mode is hosted by Box)	Tools land directly in the Agent's tool list	Connect an existing MCP service
Plugin	Plugin Runtime	Capabilities are exposed through the plugin system	Long-lived capability with a config page, event listeners, or knowledge components

Pipeline Binding

Skills, MCP Servers, and plugins are all pipeline extensions. After installing or creating them in the WebUI, the pipeline extension config still decides where they're enabled:

• Enable all extensions, or
• Bind only specific extensions

Skill binding decides which skills the Agent can see (it controls the <available_skills> list). The actual skill content is only injected after the Agent calls activate.

Troubleshooting Map

Symptom	Check first
Agent has no exec/read/write tools	box.enabled, backend availability, and whether the pipeline uses the built-in Agent
Skill list is empty	Box Runtime status, box.local.skills_root, pipeline binding
stdio MCP fails to start	Box Runtime status, MCP command and environment variables, startup timeout
Sandbox fails to start in Docker deployment	Whether langbot_box mounts docker.sock, and whether Box root paths match
File read/write fails	box.local.host_root, box.local.allowed_mount_roots
Backend selection has no effect	Confirm BOX__BACKEND is set on the langbot service, not on langbot_box

Note

Sandbox built-in tools and Skills currently target the built-in Agent. External runners (Dify, n8n, Langflow, Coze, etc.) should use their own tools and execution model.