"A guide to finding people on LinkedIn by their name" matching MCP servers:

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

Enables sentiment analysis of text blocks using the Api Ninjas API, returning sentiment scores and overall sentiment classification for up to 2000 characters of text.

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

A simple note storage system that lets users create and summarize notes with varying detail levels using Claude.

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

Provides clean, bounded web content to AI by filtering HTML noise and optionally summarizing, preventing context window overflow.

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 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.

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).

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.

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

Routes narrow text-processing tools (classification, extraction, summarization, etc.) to budget models to reduce token consumption on the main model.

Precise character-level string indexing for LLMs. Provides tools for finding, extracting, and manipulating text by exact character position to solve position-based operations.

Provides intelligent transcript processing capabilities for Claude, featuring natural formatting, contextual repair, and smart summarization powered by Deep Thinking LLMs.

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

A TypeScript-based MCP server built on the Gmail API that implements a simple notes system. It enables users to create, manage, and summarize text-based notes through specialized resources and tools.

A simple note storage system that allows creating, storing, and summarizing notes with customizable detail levels.