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    Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.
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    Apache 2.0
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    AI-powered multi-voice audiobook creation platform. Provides tools for pricing, language support, use cases, onboarding, FAQ, alternatives comparison, and cost estimation. npx echo3s-mcp
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    MIT
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    An MCP server for interacting with the USAspending.gov API, supporting local use with Claude Desktop and cloud deployment with login.gov authentication.
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    Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.
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    MIT
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    Enables LLM clients to execute shell commands safely through the MCP protocol, with features like session management, safe mode, and process control.
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    Apache 2.0
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    What is PandaDoc MCP? PandaDoc MCP (Model Context Protocol) server connects AI agents directly to PandaDoc's document workflow — creating, sending, and tracking contracts and agreements without leaving your AI client. How to use PandaDoc MCP? To use PandaDoc MCP, connect your PandaDoc account, provide the required API credentials, and configure the appropriate MCP client.
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    MIT
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    An MCP server for external computer-use that launches, observes, and interacts with any X11 application via AT-SPI2 accessibility tree and xdotool input injection.
    MIT
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    Enables AI agents to create and manage payment links programmatically via the Global Payments API, supporting single-use and multi-use links, retrieval, and API documentation retrieval.
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    GPL 2.0
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    An MCP server for the iNavi Maps API that gives AI assistants iNavi Maps API specifications and ready-to-use HTML templates for interactive map visualizations (geocoding, POI search, route planning).
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    MIT
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    Call, text, or push your phone when an agent needs input mid-task — reply by voice instead of babysitting a long-running or blocked terminal.
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    MIT
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    Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.
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