Remote Suite
FreeNot checkedA production-ready Model Context Protocol suite over Streamable HTTP providing a sandboxed file server with tools, resources, prompts, and both manual and AI-dr
About
A production-ready Model Context Protocol suite over Streamable HTTP providing a sandboxed file server with tools, resources, prompts, and both manual and AI-driven clients.
README
A production-ready Model Context Protocol (MCP) suite over Streamable HTTP, demonstrating remote connectivity, a filesystem roots security boundary, and where sampling (server-initiated LLM requests) fits in.
It ships three runnable apps on top of one transport layer:
| Component | Role | Default URL |
|---|---|---|
Server (mcp-server) |
FastMCP file server: tools, resources, prompts, sandboxed to a workspace root | http://127.0.0.1:8000 |
GUI client (mcp-gui) |
Manual Gradio UI to discover/run tools, read resources, render prompts | http://127.0.0.1:7861 |
AI host (mcp-host) |
Gradio chat where an OpenAI model drives the MCP tools | http://127.0.0.1:7862 |
Architecture
src/mcp_remote_suite/
├── config.py # env-driven settings (pydantic-settings)
├── logging_config.py # shared logging setup
├── _content.py # unwrap MCP result objects -> text/dicts
├── server/
│ ├── security.py # WorkspaceGuard — path-traversal protection
│ ├── files.py # WorkspaceFiles — testable file operations
│ ├── app.py # FastMCP factory + entry point
│ └── __main__.py # python -m mcp_remote_suite.server
├── client/
│ └── base.py # MCPHTTPClient — transport only, no UI/LLM deps
└── apps/
├── gui.py # MCPHTTPClientApp (manual)
└── host.py # MCPHTTPHostApp (LLM-driven, multi-round tool loop)
tests/ # pytest unit tests for the security boundary + files
Layering: apps depend on client and _content; server depends on
security + files. Nothing hardcodes ports/URLs/models — all configuration
flows from config.py.
Setup
python -m venv .venv
# Windows: .venv\Scripts\activate | Unix: source .venv/bin/activate
pip install -e ".[dev]"
cp .env.example .env # optional — adjust ports, model, OpenAI creds
Run
Start the server, then either app (each in its own terminal):
mcp-server # http://127.0.0.1:8000
mcp-gui # http://127.0.0.1:7861 (manual)
mcp-host # http://127.0.0.1:7862 (AI chat; needs OpenAI creds)
Equivalent module form: python -m mcp_remote_suite.server, etc.
Configuration
All settings come from environment variables or .env (see .env.example).
Key ones: SERVER_HOST/SERVER_PORT, WORKSPACE_DIR, SERVER_URL,
GUI_PORT/HOST_PORT, LOG_LEVEL, and OPENAI_API_KEY / OPENAI_BASE_URL /
OPENAI_MODEL for the AI host.
Security boundary
Every server-side path goes through WorkspaceGuard.resolve(), which resolves
the path and rejects anything escaping the workspace root (.., absolute paths,
symlink escapes) with AccessDeniedError. This is the "roots" enforcement that
makes the server safe to expose remotely.
Tests
pytest
Install Remote Suite in Claude Desktop, Claude Code & Cursor
unyly install mcp-remote-suiteInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add mcp-remote-suite -- uvx --from git+https://github.com/TanvirIslam-BD/mcp-remote-suite mcp-remote-suiteFAQ
Is Remote Suite MCP free?
Yes, Remote Suite MCP is free — one-click install via Unyly at no cost.
Does Remote Suite need an API key?
No, Remote Suite runs without API keys or environment variables.
Is Remote Suite hosted or self-hosted?
A hosted option is available: Unyly runs the server in the cloud, no local setup required.
How do I install Remote Suite in Claude Desktop, Claude Code or Cursor?
Open Remote Suite on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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