"A guide for using sentiment analysis to identify investment opportunities" matching MCP servers:

Turkish sentiment anlaysis with MCP

A lightweight Gradio application that analyzes text for sentiment (positive/negative) and sarcasm detection using Hugging Face Transformers, designed to run on CPU and compatible with the MCP server architecture.

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.

Algorithmic text and NLP analysis server providing sentiment, readability, keyword extraction, language detection, stats, and more via REST and MCP.

Search Google News and analyze sentiment through a fixed tool chain, returning JSON, Markdown reports, and final summaries.

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.

Enables analysis of YouTube videos using the Gemini API to generate summaries and answer specific questions via direct URLs. It supports standard videos and shorts, allowing users to interact with video content without requiring manual downloads.

Enables intelligent web searching using SearXNG with content crawling via Creeper, then summarizes webpage content using LLM to avoid token limit issues. Supports smart filtering with domain blacklist/whitelist and optional LLM-based relevance filtering.

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

Provides tools for fetching real-time news and performing AI-powered sentiment analysis and summarization using Mistral AI. It enables users to analyze news trends and extract structured insights through natural language queries.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

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.

Provides tools for text file analysis, including metrics like word counts and character frequencies, alongside file reading and directory browsing capabilities. This server enables LLMs to interact with and process local file content securely through the Model Context Protocol.

Analyzes sentiment in news headlines from major US publications using both standard and natural language date inputs, enabling insights into public sentiment trends.

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

A Model Context Protocol server that provides document analysis capabilities to LLM applications, including extraction, chunking, summarization, and semantic search for PDF, DOCX, and plaintext documents.

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.

A local-first Codex plugin that bundles an MCP server to safely interact with Mattermost, enabling channel/thread summarization, conversation search, and reviewed post publishing via the Mattermost REST API.

Enables natural language management of Gmail through MCP tools for searching, analyzing, summarizing, drafting, and sending emails, with AI reasoning and user confirmation for actions.

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