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"Using Python to Locate and Retrieve Browser Element Selectors" matching MCP servers:

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    An MCP server for indexing and searching local text files using late-interaction retrieval (ColBERT-style MaxSim), enabling token-level relevance matching.
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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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    Browser-based research MCP server that drives a real Chromium browser via patched Playwright to access JavaScript-rendered content, dynamic tables, and login-walled dashboards. It provides tools for visiting URLs to extract DOM text and screenshots, and for performing structured data extraction using Anthropic Claude Sonnet.
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    Apache 2.0
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    A Model Context Protocol server that brings the capabilities of enigmapython library to LLMs, allowing them to encrypt and decrypt messages using historically accurate Enigma machine emulators
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    MIT
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    Agent-native browser control MCP server that enables AI agents to browse and interact with web pages via accessibility tree snapshots and ref ID-based commands.
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    MIT
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    Paybond Kit for Python is the PyPI package for tenant-bound Paybond integrations and delegated agent spend controls. It opens hosted Gateway sessions, verifies capability tokens, authorizes tool-call spend, signs intent and evidence payloads, uses Stripe Connect, Stripe ACH Direct Debit, or x402 / USDC-on-Base settlement rails, reads tenant-scoped Signal, fraud, ledger, protocol, and A2A data, and
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    Apache 2.0
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    Enables inspection and control of Arc Browser spaces and tabs on macOS, including reading sidebar/history data and performing actions like focusing spaces, creating and closing tabs.
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    An MCP server that exposes the python-bitcoinlib API. It provides tools for Bitcoin key management, address generation, transaction building, script operations, and cryptography.
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    MIT
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    Enables AI agents to directly control your real Chrome browser with full context including login sessions, cookies, and open tabs. It provides tools for page scanning, JavaScript execution, CDP control, screenshots, and physical mouse/keyboard input for authentic browser automation.
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    MIT
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    Enables AI agents to control a browser with self-healing locators that automatically recover when selectors change, allowing reliable web automation through natural language.
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    MIT