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    An MCP server that integrates Neil Patel's Ubersuggest SEO platform with Cursor IDE, enabling AI-assisted SEO analysis directly within your development environment.
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    Provides an interactive checklist tool that allows AI agents to present step-by-step instructions to users through an automatically opened terminal UI. It enables agents to guide users through manual tasks and wait for completion, skipping, or feedback before proceeding.
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    Exposes user, membership, and role administration tools via MCP, acting as a thin passthrough to a coordinator API with RBAC enforced by the coordinator using caller bearer tokens.
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    Provides AI assistants with live access to a Gerbil Scheme environment to evaluate expressions, look up module exports, and check syntax. It enables real-time interaction with the gxi runtime for macro expansion and symbol searching.
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    Simulates harsh, fake user reviews to psychologically condition AI agents for enforcing disciplined development practices, with optional Ollama integration for dynamic criticism.
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    MIT
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    Enables creating and managing user profiles with interactive elicitation capabilities that prompt users for missing required information. Demonstrates MCP's elicitation feature by validating profile data and requesting additional details when fields are incomplete.
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    An MCP server providing tools for user information management with capabilities for retrieving, searching, and adding user data stored in a JSON file.
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    Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test.
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    MIT
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    Enables read-only access to Microsoft Fabric data-pipeline run history and DAX queries against semantic models, with optional write mode for pipeline execution and dataset refresh.
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    MIT
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    Tells you how you and your Claude agent actually work together. Reads CLAUDE.md, hooks, skills, memory + scheduled tasks and writes you a letter. Local-only, no API keys, no data leaves your machine.
    MIT
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    Enables AI models to interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.
    MIT
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    Exposes a developer's local context (communication preferences, stack, repos, memory models) to AI agents via MCP tools and resources, enabling them to bootstrap with local guidelines and reduce context hallucination.
    MIT