"author:github" matching MCP servers:

Enables AI agents to perform web searches and extract full-text content from web pages via standard MCP tools, with fallback search and semantic reranking.

Enables MCP-compatible AI assistants to run Python code on Google Colab GPU/TPU runtimes, supporting accelerators like T4, A100, H100, with background execution and Google Drive integration.

Enables AI clients to create and manage tasks via a local REST API by converting natural language into HTTP requests through the Model Context Protocol.

Enables MCP clients to run seven local text and data utilities, including JSON formatting, CSV inspection, text analysis and diffing, hashing, timestamp conversion, and URL component parsing. Everything runs offline in memory with no API keys, models, or outbound requests.

Enables local-first expense logging, editing, and analysis through natural language conversation, backed by a SQLite database and accessible via MCP over stdio.

Provides secure, read-only access to Bing Webmaster Tools analytics and non-destructive URL submission for indexing, without destructive site management capabilities.

A learning MCP server providing synthetic FHIR patient data with read tools and a gated write workflow (propose → human approve → commit) with structured audit logging.

Enables secure task CRUD operations on SQLite or MySQL databases with input validation, parameterized queries, audit events, transactions, and signed delete confirmation.

Enables MCP clients to discover and fetch skills, agents, commands, and hooks from the Gen-e2 Lab Registry, and check local inventory compliance against the registry.

Gives an AI assistant full control of a real Telegram user account over MTProto, enabling it to read chats, search history, send and manage messages, and dynamically create new tools as needed.

Enables multi-agent system auditing with seven-layer analysis, cost governance, compliance mapping, and watchdog monitoring. Offers tools for audit execution, cost analysis, report verification, regulation lookup, remediation suggestions, and fix tracking.

Enables LLMs to interact with OpenEHR electronic health record systems by retrieving clinical archetypes, generating AQL queries from natural language, and executing queries against on-premise EHR databases. Supports OpenEHR Clinical Knowledge Manager integration and custom IIS-hosted EHR APIs for comprehensive medical data access.

Transforms stdio-based task tools into a stateful Streamable HTTP MCP server, enabling multiple clients to manage tasks via URL with session isolation and security checks.