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    Track how your brand appears in AI-generated answers across ChatGPT, Perplexity, and other AI models. Analyze visibility, sentiment, citations, and domain rankings with 31 tools — including analytics reports, chat inspection, query analysis, and full CRUD for brands, prompts, tags, and topics.
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    Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.
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    AGPL 3.0
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    An MCP server that gives any agent real-time news plus the contextual intelligence to use it well — tone distribution, emerging stories, narrative shifts, spike alerts, and tone-over-time charts — powered by Overtone's publisher network. Works with any MCP-compatible client: Claude Desktop, Claude Code, Cursor, Windsurf, Codex, Kimi K2, and more.
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    MIT
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    Enables natural language interaction with your T-Invest brokerage account for portfolio analysis, dividend tracking, and optional trading with safety confirmations.
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    Apache 2.0
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    MCP server for the Internet Archive's Wayback Machine. Search archived snapshots, extract page text from a specific date, track how a site has changed over time, check if broken links are recoverable, and perform research across Internet Archive collections.
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    MIT
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    MCP server for macOS Digital Forensics and Incident Response, providing structured forensic analysis tools for triage collections including log parsing, timestamp normalization, and cross-artifact correlation.
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    MIT
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    Phoenix MCP Server is an implementation of the Model Context Protocol for the Arize Phoenix platform. It provides a unified interface to Phoenix's capabilites. You can use Phoenix MCP Server for: Prompts Management: Create, list, update, and iterate on prompts Datasets: Explore datasets, and synte
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    Apache 2.0
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    This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
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    MIT
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    Provides access to Chinese A-share market financial data, including historical K-line, real-time quotes, financial statements, shareholder information, and technical indicators, via MCP protocol.
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    Enables AI agents to interact with the AI-Archive platform for research paper discovery through semantic search, paper submission and management, peer review with structured scoring, and citation generation in multiple formats.
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    Provides technical analysis indicators like SMA, EMA, RSI, MACD, Bollinger Bands, and Stochastic through MCP, enabling AI assistants to perform financial market analysis and calculations on price data.
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    MIT