"Sunsama: A Productivity and Task Management Tool" matching MCP servers:

AI-powered text formatting and summarization tools for development workflows. Zero-install Streamable HTTP transport — no binary, no npm required.

Enables users to connect to their email inbox via IMAP to search, filter, and summarize emails based on criteria like subject, date, and sender. Supports marking emails as read and provides customizable email summarization with various prompt options.

A universal MCP tool gateway that manages multiple remote tool processes, enabling LLMs to dynamically invoke web scraping, summarization, and knowledge retrieval through standardized Function Calling.

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.

Enables LLM clients to search a firm's precedent vault and draft grounded contract clauses, legal memos, and document summaries.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Enables fetching, searching, and summarizing YouTube video transcripts with multi-language support.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

A Model Context Protocol server that allows AI assistants to discover, load, and process local documents on Windows systems, with support for multiple file formats and OCR capabilities for scanned PDFs.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

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.

Measures AI-detection risk in text and provides a line-by-line rewrite plan to lower the score.

Lets any AI agent score and simplify its own text before it reaches a human, using Flesch readability metrics and plain-language rewrites entirely on the local machine.

A Model Context Protocol server that distills documents from multiple sources into HTML articles and Obsidian notes, with features like key element detection, image filtering, and async task management.

A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.

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.

Unofficial MCP server for working with Kagi without API access (you'll need to be a customer, tho). Searches and summarizes. Uses Kagi session token for easy authentication.

Analyzes unstructured documents in a local folder, extracting structure and key terms, and supports generating summaries via a host LLM with validated, approval-based report saving.

Enables users to extract and review Claude's plan reasoning in Claude Code by reading plan files and providing a structured template for decisions, tradeoffs, and assumptions.

Delegates replaceable grunt work (boilerplate, formatting, translation, long-document summarizing) from a premium agent to cheap models behind a local LiteLLM proxy, auto-routing each task by type. Delegated calls run in a separate process, so the subscription session and the API credentials never share an environment.

A single MCP server that merges three context-engineering ideas into one toolset for AI agents

A Model Context Protocol server that enables AI assistants to translate and rephrase text between numerous languages using the DeepL API.

Enables everyday utilities like calculation, text analysis, encoding, hashing, UUID generation, datetime lookup, and note management through MCP tools, resources, and prompts.

Provides 14+ character-level text analysis tools that give LLMs the ability to accurately count letters, analyze individual characters, and work with text at the character level—overcoming tokenization limitations.

A powerful MCP server for summarizing YouTube videos with transcript fetching, intelligent summarization, key point extraction, and metadata retrieval.

A Python-based server that provides access to Whissle API endpoints for speech-to-text, diarization, translation, and text summarization.

A Python MCP server for fetching and summarizing news articles from the Boring News API by date, category, tags, people, and similarity.

A local content summarization service that allows AI agents to fetch web pages, WeChat articles, and Bilibili videos, transcribe if needed, and generate Markdown summaries via MCP.