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    Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.
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    MIT
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    A VSCode and Cursor extension that captures real-time terminal output and exposes it to AI assistants via the Model Context Protocol. It enables agents to proactively monitor logs, command execution, and errors without requiring manual copy-pasting from the user.
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    MIT
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    Developers: Search your zsh, bash, or fish shell history from Claude Code, Cline, Cursor, Zed, or any MCP client using tools like search_history (full-text with timestamp/CWD/exit code), recent_in_dir, failed_commands, and command_chains for multi-step sequences. Reindex after new activity. Local-only SQLite FTS5 with secrets redacted before storage.
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    Enables AI agents to spawn persistent terminal sessions, send keystrokes, read screen state, and assert output, allowing them to interact with stateful terminal applications like vim, htop, and gdb.
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    MIT
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    Enables AI assistants to create and manage persistent terminal sessions that continue running even after disconnection, with features like smart output management, web UI visualization, and automatic bug fixing with Codex integration.
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    MIT
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    Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.
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    Enables AI agents to launch, monitor, and manage long-running terminal processes with real-time log capture and search functionality. It features automatic log rotation and graceful process termination to ensure system stability.
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    A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.
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    MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution
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    MIT
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    A demonstration MCP server that provides calculator functionality through both stdio and FastAPI implementations. Enables users to perform mathematical calculations via MCP tools using the FastMCP framework.
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    Enables AI assistants to search, compare, and get detailed information about MCP servers from the mcpcatalogs.com directory.
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    MIT