What is All-In-One MCP?

All-In-One MCP is a Model Context Protocol server designed to enhance developer workflows by providing AI-powered search, RAG capabilities, and integrations for services like GitLab, Jira, and Confluence.

How do I install and configure All-In-One MCP?

You can install it via Smithery for automated setup or manually using Go. Manual setup requires configuring a `.env` file with necessary API keys and tokens for the services you want to integrate.

What integrations does All-In-One MCP offer?

It integrates with GitLab, Jira, Confluence, YouTube, and various Google services (Calendar, Chat, Gmail), offering a unified platform for accessing and managing information across these tools.

What are the benefits of using the Deepseek AI integration?

The Deepseek AI integration provides advanced reasoning capabilities, enabling the MCP server to perform multi-step problem-solving, critical analysis, and strategic decision support within your development workflows.

What is RAG and how does All-In-One MCP use it?

RAG (Retrieval-Augmented Generation) enhances AI search by retrieving relevant information from integrated sources and using it to provide more contextual and accurate responses to queries.

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All-In-One

Name: All-In-One
Author: nguyenvanduocit

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Provides an all-in-one Model Context Protocol (MCP) server with AI search, RAG, and integrations for services like GitLab, Jira, and Confluence.

About

This project offers an all-in-one Model Context Protocol (MCP) server implementation designed to enhance development workflows with AI-powered capabilities. It integrates with various services such as GitLab, Jira, Confluence, and YouTube, providing AI-driven search and a suite of utility tools. The server supports features like RAG (Retrieval-Augmented Generation) and offers tools for developers, researchers, and general utility, aiming to streamline AI-enhanced development processes.

Key Features

Integrations with GitLab, Jira, Confluence, and YouTube
45 GitHub stars
AI-powered search across integrated services
Support for Deepseek AI tools for advanced reasoning
RAG (Retrieval-Augmented Generation) capabilities for enhanced context
Tools for managing Google services like Calendar, Chat, and Gmail

Use Cases

Integration of AI search and RAG into existing development environments
AI-enhanced development workflows
Context-aware AI assistance for developers