"Categorizing messages such as emails or system logs" matching MCP servers:

MCP server for reading and responding to local macOS Messages from clients like Claude Desktop and Codex.

Local MCP server that exposes iTerm2 tab/session logs to MCP-capable agents via AppleScript, enabling tools to list open tabs and retrieve terminal scrollback.

Enables Claude on macOS to read, search, and send iMessage, SMS, and RCS messages, with tools for stats, chat history, attachments, and message composition.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

Exposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.

MCP server for querying and analyzing logs from VMware Aria Operations for Logs, enabling log search, incident detection, and vROps correlation.

Enables LLMs to explore and analyze UK Government BEIS inspect_ai evaluation logs directly from tools like Claude Code and Cursor. It provides capabilities to list logs, view evaluation summaries, and inspect conversation histories for specific samples.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.

Enables AI agents to analyze ROS2 log files across multiple nodes by merging them into a unified timeline and providing smart query tools, without requiring ROS2 installation.

Delegates work from MCP clients (like Claude Code) to the Codex CLI, allowing spawning of autonomous Codex subagents for tasks.

Bridges a remote, cloud-hosted agent to your local machine, exposing Pi's coding tools (read, write, edit, ls, grep, find, bash, powershell) rooted at a directory you choose. It also adds a human channel so the agent can message, question, and wait on you through tool calls instead of a platform chat UI, with OAuth 2.1 or bearer-token authorization and no persistence between runs.

A Python bridge for interacting with the macOS Messages app using MCP (Multiple Context Protocol). Simple install using uvx mac-messages-mcp

Enables log analysis for Tenable Patch Management (SaaS and on-prem) by parsing, de-duplicating, and decoding server/client logs into structured verdicts, ranked issues, and known-issue fixes.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Enables MCP clients to generate and edit images through Codex's built-in image generation using a ChatGPT login, returning final files with metadata and optional inline previews.

Enables an AI assistant to author sentence-synced, motion-graphics lessons: it writes and validates lesson JSON, runs example code to verify output, renders 3D illustrations with Blender hotspots, synthesizes multi-voice narration with timing data, and builds a single-file HTML textbook. Supports any subject, from math and science to English and programming.

Enables AI coding agents to discover, compare, select, and enforce design systems and component libraries, with installation guidance, component APIs, and strict adherence directives to prevent default substitutions.

Helps founders and teams review business workflows, identify AI opportunities, assess trust/control risks, and recommend a safe first AI-human workflow.

Exposes system telemetry tools to retrieve CPU, memory, disk, battery, network, process, and GPU metrics from a local machine.