"Running queries in Apache Superset" matching MCP servers:

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.

MCP server for koreafilings.com — AI-summarized Korean DART (전자공시) corporate disclosures, paid per call in USDC via the x402 protocol on Base. Tools: get_pricing (free), get_disclosure_summary (0.005 USDC).

Youtube, readable in AI chats.

An MCP (Model Context Protocol) server specialized in deciphering PDF internal structures.

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 AI agents and MCP clients to browse Roomtone meeting notes, add YouTube or pasted-text sources, generate summaries, ask questions answered from transcripts, and retrieve raw transcript text. Recording itself stays in the Roomtone app, so the server only reads and adds to existing meetings.

MCP server for HumanPen that lets AI agents work on real documents (.docx, .pptx, .pdf) — humanizing content to lower AI-detection scores, converting citations, condensing, and translating while preserving formatting, tables, images, and citations.

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.

Provides accurate meeting transcription with speaker diarization and multilingual support, allowing users to submit audio URLs, poll transcription status, get transcripts, and summarize via MCP tools in their IDE.

Enables AI assistants to transcribe links (YouTube, Google Drive, Dropbox), list and search your recordings for spoken words and moments, and read transcripts in json/txt/srt/vtt, summaries and metadata. It also lets them request new summaries and delete recordings, all through your own account with API-key or OAuth sign-in.

This MCP server enables AI assistants to perform calculations, fetch live weather, manage in-memory notes, access system info and note resources, and use reusable code review and summarization prompts.

Stdio MCP server over the Briefing Service REST API: hourly LLM-ranked news briefings (AI, frontier labs, markets, sports, world) as structured JSON, rendered e-ink pages and a free provenance dump. Six read-only HTTPS tools, no shell, no secrets required; Dockerfile and glama.json in the repo root.

A personal MCP for WhatsApp, with voice-note and call transcripts. Search and summarize your chats, read what was said in voice notes and calls, and organize chats, labels, notes, reminders and scheduled messages. Runs locally with the Kaption extension for WhatsApp Web (Chrome, Edge) or the Kaption desktop app. No send-now tool. Setup: https://kaptionai.com/mcp/

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

Access 50+ AI-generated book summaries and chapter breakdowns directly in Claude Desktop. Search books by title, author, or ISBN, and get instant access to key insights from business, self-help, and educational books.

A Model Context Protocol server that enables access to YouTube video content through transcripts, translations, summaries, and subtitle generation in various languages.

Enables AI assistants to read, search, create, and organize notes in an Obsidian vault, with features like summarization and daily most valuable notes identification.

Provides fast, multilingual spell-checking for text and files, featuring syntax-aware parsing that intelligently checks only comments and strings in code. It supports over 15 languages and enables directory-wide scanning with custom dictionary management.

Transforms chat conversations with AI into structured markdown summaries and automatically saves them to organized files in your notes directory. Supports different summary styles, handles large conversations through chunking, and provides tools to manage your saved summaries.

Enables complex queries over data on the DANDI Archive and provides a system for managing text notes. It features tools for note creation, resources for note access via custom URIs, and prompts for generating summaries.

Enables delegating narrow tasks such as classification, schema-based extraction, and summarization to local models running through Ollama or LM Studio, with code-validated structured outputs.

Counts characters and words in both Japanese and English text files, with special handling for Japanese morphological analysis and proper character counting excluding spaces and line breaks.

Analyzes survey comments from CSV files using morphological analysis and AI to generate interactive HTML dashboards with word clouds, keyword rankings, and actionable insights in Japanese or English.

An MCP server that enables users to generate summaries of YouTube videos in multiple languages and formats through integration with DeepSRT's API.

A local-first MCP server that lets agents search and summarize a user's own WeChat history, with stable pagination, bulk chat workflows, unread/event queries, and gated enrichment tools.

Enables AI assistants to analyze and summarize YouTube videos by extracting captions, subtitles, and comprehensive metadata including title, description, and duration in multiple languages.

Wraps the gpt-researcher tool as an MCP server, enabling automated web research, information summarization, and structured report generation via natural language queries.

Enables automatic validation and correction of Re:VIEW manuscript files by checking for unauthorized tags, fixing duplicate/empty IDs, and running fast lint checks to prevent common errors during writing.