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    Provides AI-powered educational tools for teachers including lesson planning, quiz creation, student progress analysis, learning path recommendations, and rubric generation. Enables educators to automate administrative tasks and personalize learning experiences through natural language interactions.
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    MIT
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    Enables natural-language queries about real filming locations and the productions recorded at them, including search, proximity, and ranking tools.
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    MIT
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    IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real
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    JavaScript
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    A persistent memory system for Large Language Models (LLMs) that enables continuous learning and knowledge retention across sessions through the Model Context Protocol (MCP).
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    Provides linear programming (LP), mixed-integer programming (MIP), and quadratic programming (QP) optimization capabilities using the HiGHS solver, enabling AI assistants to solve complex optimization problems like production planning, logistics, and portfolio optimization.
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    MIT
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    Self-learning memory for AI coding agents. Observes tool sequences, user preferences, and recurring fixes — auto-promotes high-confidence patterns into behavioral rules. 22 tools, 2 prompts, SQLite-backed, zero config.
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    MIT
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    Enables natural language queries about the technologies behind websites and the companies running them, using the StackScan Tech Lookup API. Includes tools for domain technology lookup, company details, technology usage stats, and batch company lookups.
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    An MCP server that connects language models to a Wazuh SIEM cluster, enabling read-only plain-language queries, schema inspection, field coverage analysis, and decoder testing.
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    Apache 2.0
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    Contract-first programming language with a local MCP server for checking types, effects, capabilities, and contracts in agent-written modules. Its review tool compares before and after source sets and returns receipts for new authority, weaker promise tiers, and new Guarded runtime obligations.
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    Apache 2.0
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    MCP server that scores the behavioral risk of a wallet on Base before sending it money. Provides a risk score, verdict, and explainable flags based on USDC payment history.
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    Apache 2.0
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    Enables AI agents to check news against live Polymarket markets, retrieve market odds, and manage trades including placing, selling, and canceling orders.
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    MIT
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    A local AST and type-aware Go repository context indexer that uses CHA to map symbols, call graphs, dependencies, and architecture patterns. Built for AI coding agents that need to navigate and reason about large Go codebases without reading raw files.
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    MIT
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    An enhanced sequential thinking tool optimized for programming tasks that helps break down complex coding problems into structured, self-auditing thought steps with branching and revision capabilities.
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    MIT
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    Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.
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    MIT