MCP Command Bridge

Full container control bridge for mobile MCP clients (RikkaHub, etc.).

This project exposes MCP tools that let an AI agent run shell commands, execute programs, manage files, make HTTP requests, and install packages inside a Docker container sandbox. The container IS the sandbox — the agent has full control inside it, with all operations audit-logged and workspace data persisted to the host.

Works on Windows and Linux (VPS). Deploy to a VPS with the one-click script for secure remote access from your phone.

Features

Core Tools

• run_shell(command) — PREFERRED tool. Execute shell command strings directly via bash -c. Supports pipes (|), redirects (>), chaining (&&, ||), env vars ($HOME), globs (*), and all bash syntax. No need to write scripts to files first.
• run_program(program, args) — Structured argv execution (shell=False). Use when you need precise control without shell interpretation.
• run_workspace_script(runtime, path) — Run a script file from the workspace.
• get_policy() / get_capability_details(name) — Capability discovery for the LLM.

Task Tools

• HTTP: http_probe(url), fetch_url(url)
• Network: ping_host, dns_lookup, tcp_probe, trace_route
• System: system_snapshot()
• Files: list_files, read_file, write_file, append_file, make_directory

Security & Infrastructure

• Streamable HTTP MCP server at /mcp (mobile-compatible: no DNS rebinding / Origin checks).
• Bearer token auth + optional IP allowlist + rate limiting.
• Environment variable override for token and secrets (MCB_TOKEN, MCB_SECRET_*).
• Full UTF-8 encoding support — Chinese and other non-ASCII text works out of the box.
• JSONL audit logging of all operations to data/logs/audit.jsonl (host-mapped).
• Secret placeholder replacement and masking in outputs and logs.
• Timeout and output truncation.

Data Persistence

Container path	Host path	Purpose
/app/agent_workspace	data/workspace/	Agent's writable workspace
/app/projects	data/projects/	Cloned repos and project files
/app/logs/audit.jsonl	data/logs/audit.jsonl	Audit log of all operations

Files saved outside these paths are ephemeral and will be lost on container restart.

Install

pip install -e .

Configure

Start from config.example.yaml (LAN) or config.vps.yaml (VPS).

Important fields:

• server.token: required Bearer token (or set MCB_TOKEN env var).
• server.allowed_origins: accepted browser/client origins.
• server.ip_allowlist: optional IP restriction (empty = allow all).
• server.rate_limit_per_minute: app-level rate limit (0 = unlimited).
• server.compact_toolset: expose compact grouped tools instead of many granular tools.
• execution.allowed_roots: directories commands may run inside.
• execution.writable_roots: directories MCP clients may create and edit files inside.
• programs.<name>.enabled: whether a program is callable.
• secrets: values available through ${NAME} placeholders (or MCB_SECRET_<NAME> env vars).

Run

python -m mcp_command_bridge.server --config config.example.yaml

The default sample config listens on:

http://127.0.0.1:8765/mcp

For LAN use, keep server.host: "0.0.0.0" in the config and connect from the phone to:

http://<computer-lan-ip>:8765/mcp

VPS Deployment

Deploy to a VPS with Docker — port 8765 is exposed for your own reverse proxy setup:

git clone https://github.com/XD06/MCP_Command_Bridge.git
cd MCP_Command_Bridge
sudo bash deploy/deploy.sh --domain mcp.yourdomain.com

The script installs Docker, generates a strong token, builds the container, and exposes port 8765. A reference Nginx config (TLS + rate limiting + security headers) is at deploy/nginx/mcp-command-bridge.conf — set up your own Nginx/Caddy for TLS and domain routing. Data (workspace, audit logs) is mapped to the host for easy access.

See docs/vps-deployment.md for full details.

Send:

Authorization: Bearer <server.token>

Test

python -m unittest discover -s tests

Current result:

95 tests passed

Security Model

Container Full-Control Mode (VPS)

In VPS/Docker deployment, the container IS the sandbox:

• run_shell and run_program are exposed with no restrictions on URLs, methods, paths, or arguments.
• The agent can apt-get install, pip install, git clone, write scripts, and execute them.
• Isolation comes from Docker resource limits, not application-level restrictions.
• All operations are audit-logged to data/logs/audit.jsonl (host-mapped).

Restricted Mode (LAN)

run_program and run_shell are hidden by default (server.expose_advanced_tools: false). File tools are restricted to execution.writable_roots. This mode is for local development.

Encoding

All subprocess I/O uses hardcoded UTF-8 encoding (encoding="utf-8", errors="replace"). The Docker container sets LANG=C.UTF-8, LC_ALL=C.UTF-8, PYTHONUTF8=1, PYTHONIOENCODING=utf-8. Chinese and other non-ASCII text works without errors.

Tool Selection Guide

• run_shell(command) — PREFERRED for most tasks. Pipes, redirects, chaining, inline code.
• http_probe(url) / fetch_url(url) — Quick HTTP status / text fetch.
• ping_host, dns_lookup, tcp_probe, trace_route — Network diagnostics.
• system_snapshot() — OS, IP, Python version info.
• write_file / read_file — Create and read workspace files.
• run_workspace_script(runtime, path) — Run a workspace script file.
• run_program(program, args) — Precise argv control without shell interpretation.

get_policy() returns a capability summary. get_capability_details(name) returns detailed rules.

server.require_capability_preflight: true forces models to call get_capability_details(name) before task tools in that capability can run.

With server.compact_toolset: true, the default tool surface is:

get_policy
get_capability_details
system_snapshot
http_request
network_check
workspace
run_workspace_script