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mcp-local-telemetry

CI PyPI Python versions License: MIT

A lightweight Model Context Protocol server that exposes local system telemetry (CPU, RAM, Disk, top processes) to MCP-aware AI agents — Claude Code, Cursor, ChatGPT Desktop, and any other MCP client.

Written as a single-file, dependency-light Python script. Ships in under 200 lines and speaks JSON-RPC 2.0 over stdio.

Why

AI coding agents are increasingly asked to reason about the machine they are running on — "is it safe to run this build?", "what's eating CPU right now?". This server gives them a structured, protocol-standard way to ask.

Related MCP server: open-monitor

Tools

Tool

Description

get_system_metrics

CPU %, memory %, disk %, load average, boot time.

get_top_processes

Top-N processes by CPU usage.

Or install from source:

git clone https://github.com/Jamie643/mcp-local-telemetry.git cd mcp-local-telemetry python -m venv .venv && source .venv/bin/activate # Windows: .venv\Scripts\activate pip install -e .

Claude Code

claude mcp add local-telemetry -- mcp-local-telemetry

Cursor / Claude Desktop (mcp.json)

{ "mcpServers": { "local-telemetry": { "command": "mcp-local-telemetry" } } }

Manual smoke test

printf '%s\n'
'{"jsonrpc":"2.0","id":1,"method":"initialize","params":{}}'
'{"jsonrpc":"2.0","method":"notifications/initialized"}'
'{"jsonrpc":"2.0","id":2,"method":"tools/list"}'
'{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"get_system_metrics","arguments":{}}}'
| mcp-local-telemetry

Development

pip install -e ".[dev]" ruff check . mypy mcp_server.py pytest

Protocol notes

Transport: JSON-RPC 2.0 over stdio, newline-delimited.

Protocol version: 2024-11-05.

Capabilities: tools only.

All logs go to stderr; stdout carries only JSON-RPC frames.

License

MIT — see LICENSE.

Commit it

git add README.md
git commit -m "Rewrite README: add badges, remove unrelated stack section, use PyPI install"
git push

## Install

```bash
pip install mcp-local-telemetry

Available Tools

2 tools
get_system_metricsGet System MetricsA

Returns current CPU, RAM, and Disk utilisation for the local machine. Useful for pre-flight checks before launching heavy builds, containers, or model inference.

Inputs: no named parameters.

get_top_processesGet Top ProcessesC

Returns the N processes with the highest CPU usage.

Inputs: limit.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.4/5.0

    Scored across 2 tools

    Disambiguation5/5

    get_system_metrics returns aggregate machine-level stats while get_top_processes returns per-process ranking, so their purposes are clearly distinct. An agent can trivially choose between them with no overlap.

    Naming Consistency5/5

    Both tools follow a consistent get_<noun> snake_case verb_noun pattern. Naming is predictable and idiomatic throughout.

    Tool Count3/5

    Two tools is on the thin side for a telemetry server; while each earns its place, the surface feels minimal and could reasonably include a couple more monitoring dimensions without bloat.

    Completeness3/5

    Core CPU/RAM/Disk and top-CPU-process coverage exists, but network I/O, memory-heavy process ranking, disk I/O, and any historical/sampling data are missing. Agents can perform basic pre-flight checks but hit dead ends for richer diagnostics.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data

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