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Nano MCP Termux

I
by io.github.Lmeng486

Zero-dependency single-file MCP server for Termux/Android, Raspberry Pi and Linux.

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Install from the publisher. Not a PlugMCP endpoint.

No packaged release in the registry yet. Follow the repository README.

Provider
Step-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

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Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

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Zero-dependency single-file MCP server for Termux/Android, Raspberry Pi and Linux.

nano-mcp-termux

Zero-dependency, single-file MCP server for AI agents, natively running on Termux (Android), Raspberry Pi, and Linux.

🚀 Quick Start

Local (Termux / Linux)

cd /path/to/nano-mcp-termux
python3 nano_mcp_termux.py

Docker

docker build -t nano-mcp-termux .
docker run -i --rm nano-mcp-termux

Health check (one-shot, no MCP handshake)

python3 nano_mcp_termux.py --health

🔌 Connect to your MCP client

This server does not run standalone — it's a sidecar that your AI client connects to via the MCP protocol.
Below are the three most common ways to mount it.

Option 1 — Zero‑install (uvx), best for desktop AI clients

uvx nano-mcp-termux

Then add this JSON to your AI client's mcpServers config (see client‑specific notes below):

{
  "mcpServers": {
    "nano-mcp-termux": {
      "command": "uvx",
      "args": ["nano-mcp-termux"]
    }
  }
}

Option 2 — Already pip installed, or you prefer a direct Python launch

pip install nano-mcp-termux

Config snippet for your AI client:

{
  "mcpServers": {
    "nano-mcp-termux": {
      "command": "nano-mcp-termux"
    }
  }
}

Option 3 — Run the single file directly (e.g. inside Termux on Android)

# Clone or download the repo, then:
cd /path/to/nano-mcp-termux
python3 nano_mcp_termux.py

Config snippet for your AI client:

{
  "mcpServers": {
    "nano-mcp-termux": {
      "command": "python3",
      "args": ["/full/path/to/nano_mcp_termux.py"]
    }
  }
}

How to use these snippets: client‑specific config files

AI clientConfig file location (examples)Note
Claude DesktopmacOS: ~/Library/Application Support/Claude/claude_desktop_config.jsonWindows: %APPDATA%\Claude\claude_desktop_config.json∆ mcpServers key at top level
Cursor~/.cursor/mcp.json∆ mcpServers key at top level
Cline$HOME/.cliner/mcp.json (or inside project folder as cline_mcp_settings.json)∆ mcpServers key at top level
Cherry StudioGUI → MCP section (typically auto‑creates ~/.cherrystudio/mcp/*.json)JSON schema as above
Operit~/.operit/mcp_config.json (or per‑workspace config in the workspace folder)∆ mcpServers key at top level

Tip: after editing the config file, restart your AI client so the new server is detected. If the client supports hot‑reload, you may not need a restart.

Troubleshooting

SymptomLikely causeFix
Client shows "server not found"command path is wrong or not in PATHUse absolute path (/usr/local/bin/nano-mcp-termux for pip installs, $HOME/.local/bin/nano-mcp-termux for pip --user)
Error: spawn uvx ENOENTuvx not in PATH (not installed)Use a custom shell like "shell": "uw uvx" or the direct Python launch (Option 2)
"Connection lost" / process dies immediatelyNo stdin from clientThis server is stdio‑bound; don't run it directly like nano-mcp-termux — always launch it through your client's MCP config

🛠️ Features

  • ✅ Zero-dependency: No external packages required
  • ✅ Single-file: All logic in one Python script
  • ✅ Cross-platform: Works in Termux (Android), on Raspberry Pi, Linux, and inside Docker
  • ✅ Container-ready: Dockerfile at repo root for Glama introspection
  • ✅ Standard stdio framing: Newline-delimited JSON-RPC (official MCP transport)
  • ✅ Version negotiation: Echoes client protocolVersion (2024-11-05 / 2025-06-18 / 2025-11-25), falls back to highest supported
  • ✅ Graceful degradation: device_status never fails; unavailable inputs are marked, not crashed
  • ✅ [lifecycle] No orphaned processes: every command runs in its own process group; timeouts kill the whole tree (SIGTERM → SIGKILL), never just the shell
  • ✅ [lifecycle] Self-terminating: parent-process watchdog + stdin-EOF detection + optional idle timeout, so a dead client never leaves a zombie server behind
  • ✅ [lifecycle] Phantom Process Killer aware: reports Android 12+ child-count risk with concrete mitigations
  • ✅ [paths] Android/Termux path adapter: resolves /sdcard ↔ /storage/emulated/0 ↔ $HOME/storage/shared, detects noexec mounts, case-insensitive filesystems, and shell-quoting hazards

🧩 Tools Overview

ToolDescription
device_statusAggregate device info: battery / storage / arch / memory (degraded fields marked unavailable)
server_healthRuntime health: pid/ppid/env, uptime, request counters, live children, reaping policy, RSS, Phantom Process Killer risk
resolve_pathResolve an Android/Termux path: canonical form, mount point, noexec/read-only flags, case sensitivity, equivalent spellings, quoting warnings
path_adapterEnvironment profile: runtime class, $HOME/$PREFIX/$TMPDIR, Android storage roots with mount summaries, noexec mount list

🔗 Protocol Surface

MethodBehavior
initializeEchoes supported client version (2024-11-05 / 2025-06-18 / 2025-11-25), else responds with highest supported per MCP spec; declares {"tools": {}}
notifications/initializedSilent (no response)
pingReturns {}
tools/listReturns tool catalog
tools/callReturns {"content": [{"type": "text", ...}]}
Unknown method / tool-32601 / -32602 JSON-RPC errors
Malformed JSON-32700 parse error

🔄 Why 1.1.0: the orphan-process bug

Version 1.0.0 ran commands with subprocess.run(..., timeout=...). On timeout, Python terminates only the direct child — the sh -c wrapper. Anything the shell had already spawned is reparented to init and survives forever. On Android that is the exact leak class that trips the Phantom Process Killer and can get the whole app group killed.

1.1.0 fixes this at the root: commands are spawned with start_new_session=True and torn down with os.killpg(pgid, SIGTERM) → SIGKILL, so the entire process tree dies together.

The repository ships a reproducible A/B regression test for it:

python3 test_lifecycle_orphan.py
# current  nano_mcp_termux.py           leaked_grandchildren=0
# legacy   nano_mcp_termux_v10_backup.py leaked_grandchildren=1   <- the bug
# PASS: current server leaves 0 orphaned grandchildren after timeout

✅ Tests

python3 test_client.py            # 32 protocol / tool / lifecycle assertions
python3 test_lifecycle_orphan.py  # orphan-leak A/B regression (1.0.0 vs 1.1.0)

⚙️ Environment variables

VariableDefaultPurpose
NANO_IDLE_TIMEOUT0 (off)Seconds of inactivity before the server exits on its own
NANO_NO_WATCHDOGunsetSet to 1 to disable the parent-process watchdog thread

🔗 Links

  • Original repository: Lmeng486/nano-mcp-termux
  • Verification report: awesome-termux-mcp
  • Measured overhead report (this server as subject under test, all numbers from a real device): MCP on Mobile: Measured Overhead Report

This server is designed to pass Glama introspection checks and serve as a lightweight MCP implementation for mobile and edge devices.

How do I install Nano MCP Termux?
Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.
Does Nano MCP Termux need an API key?
No required environment variable is listed on this record.
What transport does Nano MCP Termux use?
Nano MCP Termux runs locally over stdio.
When was Nano MCP Termux last checked?
Last checked 2026-10-16. Zero-dependency single-file MCP server for Termux/Android, Raspberry Pi and Linux.

No tool list yet. Remote servers get one after the first health check.

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