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

Enables semantic search, retrieval, and summarization of Gmail emails with privacy-aware classification and PII sanitization.

A Retrieval-Augmented Generation system that enables uploading, processing, and semantic search of PDF documents using vector embeddings and FAISS indexing for context-aware question answering.

Enables managing documents on the filesystem through natural language, with tools for read, create, edit, delete, and commands for summarize, format, rewrite, and convert.

An AI-powered meeting assistant that combines FastAPI backend with React frontend to generate high-quality meeting summaries and provide Q&A functionality using OpenAI and Selenium.

Extracts structured commitments (who promised what, by when, under conditions) from text transcripts, emails, Slack logs, etc. using Anthropic API.

Automatically generates comprehensive merge request summaries from git logs, analyzing commit history and categorizing changes into structured descriptions. Provides tools to analyze git repositories, compare branches, and create detailed summaries with change categorization, impact analysis, and review time estimates.

AI-powered Gmail assistant that enables email management such as reading, searching, sending, summarizing, and organizing emails via natural language.

Model Context Protocol server exposing the bankstatementparser library as first-class agent tools for reading bank statements.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

Exposes the Aporix document optimization API as an MCP tool for AI agents, enabling document compression and token/cost savings analysis.

Provides MCP-compatible AI clients with offline text analysis and rewriting tools, including statistics, extractive summaries, keywords, readability scores, case conversion, entity extraction, and diffing, all running locally without API keys or network calls.

Enables delegating checkable subtasks such as summarization, search-and-summarize, and file downloads to a local OpenAI-compatible model, with mandatory result verification and job statistics.

Analyzes YouTube videos using Google's Gemini API, allowing users to get summaries or ask questions about video content via direct URL input.

A privacy-first, zero-cost AI assistant that lets you chat with your documents locally via CLI or web app, supporting search, summarization, and Q&A using your own model.

Converts subtitles or text into a single 1080×1620 infographic card (HTML+PNG) using LLM to generate content and Puppeteer for rendering.

Enables counting characters or bytes in text with options to include or exclude whitespace. Provides a simple tool for text analysis and length measurement.

This TypeScript-based server implements a simple notes system using MCP concepts, enabling users to create, list, and summarize text notes through natural language prompts.

Enables reading and extracting content from PDF documents including text (as Markdown), images, tables, and metadata from both local files and URLs, with OCR support for scanned documents.

A TypeScript-based MCP server that implements a simple notes system, allowing users to create, access, and generate summaries of text notes via URIs and tools.

A TypeScript-based MCP server that implements a simple notes system, allowing creation and management of text notes with URIs and metadata.