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"A service for finding LinkedIn profiles by name and details" matching MCP servers:

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    An MCP server that enables users to retrieve trivia questions and answers across various categories through the API-Ninjas Trivia API. It supports customizable result limits and filtering by categories like science, history, and entertainment.
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    MIT
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    Generates Lorem Ipsum placeholder text with customizable parameters including paragraph count, length, and formatting options through the API Ninjas service.
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    MIT
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    PhysBound is a specialized "Physics Linter" for AI that deterministically validates RF and thermodynamic claims against hard physical limits, preventing hallucinations in engineering workflows.
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    MIT
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    MCP server for business-day arithmetic with country-aware holiday calendars. It offers tools to check, calculate, and list business days and holidays for over 60 countries.
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    MIT
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    A personal memory engine and MCP server that stores durable facts in markdown files managed via git, enabling hybrid search (lexical + semantic) through an MCP interface for persistent context across LLM sessions.
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    MIT
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
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    Apache 2.0
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    Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.
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    Apache 2.0
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    A minimal MCP server that enables HTTP requests with any method, headers, and body types, supporting large responses through chunked transfers with disk-backed caching.
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    MIT
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    Provides policy-based access control, incident tracking, and compliance monitoring to govern AI agent behavior. It enables organizations to enforce security rules and maintain audit trails by validating agent actions against trust levels and pattern-based policies.
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    Exposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.
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    9
    MIT