MCP Server

LangBot can call tools from MCP servers. Once an MCP server is added, the built-in Agent — with tool use enabled on its model — can invoke those tools during a conversation.

Install from LangBot Space for the smoothest setup — listed MCPs are pre-configured and ready to use.

You can also fetch from ModelScope, mcp.so, or composio.dev, then add them manually as shown below.

Three Transport Modes

Mode	When to use	Notes
Streamable HTTP (mode: "http")	Remote MCP service that speaks Streamable HTTP	LangBot connects to the remote URL directly
SSE	Remote MCP service that speaks SSE	LangBot connects to the remote URL directly
stdio	MCP server launched by a local command	Only available when Box Runtime is up

MCP tools require the pipeline to use the built-in Agent, with a model that has tool use enabled — see Models. External runners (Dify, n8n, Langflow, Coze, etc.) use their own tool mechanisms.

Installing an MCP Server

From LangBot Space (Preferred)

LangBot Space is the official LangBot marketplace, with a curated list of ready-to-use MCP servers. In the WebUI, browse and install them with one click under Plugin Management → MCP Management — URL, command, and mode are filled in by the listing, so nothing has to be configured by hand.

This covers most cases. For services that aren’t listed, use the manual flow below.

Adding Manually

Open Plugin Management → MCP Management:

Click Add in the top right, choose Add MCP Server, fill in the URL (HTTP/SSE) or command (stdio), click Test to verify connectivity, then Submit:

After saving, toggle the switch on the card to connect. Click the card to see details:

Enabling in a Pipeline

Once an MCP server is added, the pipeline extension config decides which servers the Agent can see:

• Enable “all MCP servers”, or
• Bind only specific MCP servers

Tools from unbound servers won’t appear in that pipeline’s tool list.

Advanced: stdio MCP

stdio MCP is hosted by Box Runtime. Before the connection is ready, LangBot:

1. Creates or reuses a shared MCP Box session
2. If a local project path can be inferred from the command, stages the project into the workspace
3. Installs dependencies if the project has requirements.txt, pyproject.toml, setup.py, or setup.cfg
4. Connects the MCP process’s stdin/stdout through a WebSocket relay

To fine-tune mount, network, or timeout behavior, add a box override under the MCP extra_args:

{
  "mode": "stdio",
  "extra_args": {
    "command": "python",
    "args": ["server.py"],
    "env": {},
    "box": {
      "host_path": "/path/to/mcp-project",
      "network": "on",
      "host_path_mode": "ro",
      "startup_timeout_sec": 120,
      "image": "python:3.11-slim"
    }
  }
}

Common fields:

Field	Notes
host_path	MCP project directory on the host. Must be within box.local.allowed_mount_roots
network	Whether network is allowed (typically for dependency install)
host_path_mode	Access mode when staging host_path; defaults to ro. stdio MCP usually stages into the workspace
startup_timeout_sec	Box prep + dependency install timeout, default 120s. Connection wait gets about 30s extra
image	Runtime image when the Docker backend is used

stdio MCP runs inside Box. Dependency install and process startup are subject to the sandbox profile, network permission, resource limits, and the mount allowlist.

Common Issues

Symptom	What to check
MCP connection fails	URL, command, arguments, env vars are correct
stdio MCP stuck connecting	Box Runtime status; startup_timeout_sec may be too short
Dependency install fails	Sandbox network permission; dependency files are correct
Local files inaccessible	host_path exists; it’s inside allowed_mount_roots
Agent doesn’t see MCP tools	Pipeline uses built-in Agent; model has tool use enabled; MCP is bound on the pipeline