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Enables AI assistants to interact with GitHub through a Model Context Protocol (MCP) server.
Facilitates interaction with an LLM-powered chatbot following the Model Context Protocol.
Connects AI models to Steampipe, enabling them to execute queries and retrieve data.
Builds a modern web application using Next.js for MCP server implementation.
Automates mobile test generation and management by integrating with frameworks, JIRA, and BDD methodologies.
Connects large language models to live ActiveCampaign data, enabling natural language queries through CData JDBC Drivers.
Processes Microsoft Word (.docx) documents, offering comprehensive formatting support and various conversion and analysis tools.
Establishes a Model Context Protocol (MCP) server for seamless interaction with Kogna's multi-agent AI avatar system.
Extracts code symbols like functions, classes, and structs from codebases with surgical precision for AI assistants.
Manages SQLite databases with comprehensive features for creation, table operations, data manipulation, backup, recovery, and import/export.
Automatically guards projects against known security vulnerabilities in dependencies using the OSV.dev database.
Integrates Everything (voidtools) file search with Claude Desktop to provide instant, comprehensive filesystem search capabilities on Windows.
Empowers AI to autonomously select and invoke diverse tools, facilitating automation from simple calculations to complex knowledge graph analysis using large language model function calling.
Empower AI agents to safely manage, organize, and analyze local files and directories with robust tools and configurable safety features.
Enable AI assistants to securely execute commands and transfer files on remote servers via SSH.
Provides persistent memory and context management for AI assistants across sessions.
Exposes file system utilities and markdown note management to AI assistants via the Model Context Protocol (MCP) using a JSON-RPC 2.0 stdio transport.
Fine-tune open-source large language models (LLMs) and small language models (SLMs) on custom data, providing domain-specific models with full control and managed infrastructure.
Empowers AI assistants to control Tracecat SOAR platform operations through natural language, managing workflows, actions, cases, and more.
Generates and revises PowerPoint decks from natural-language prompts and trusted sources for AI agents.
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