atlas-mcp-server is a Model Context Protocol (MCP) server built in TypeScript that leverages Neo4j’s graph database to provide intelligent project and task management. It empowers LLM agents with seamless collaboration and guidance, featuring robust tools for project management, member collaboration, dependency tracking, and whiteboard functionalities.
atlas-mcp-server is designed to manage complex projects by integrating advanced features like Neo4j-powered graph databases for efficient relationship management, real-time collaborative whiteboards, role-based access control, and standardized communication between LLMs and external systems via the MCP framework. This makes it ideal for organizations seeking scalable, high-performance project management solutions.
This tool is suitable for developers, project managers, and teams working with AI models (LLM agents) who require advanced project management capabilities, collaboration tools, and integration with graph databases. It is also beneficial for users familiar with TypeScript, Neo4j, and MCP-compatible clients.
atlas-mcp-server can be self-hosted using Docker (with docker-compose included) or deployed on Neo4j AuraDB cloud service for cloud-based solutions. Its modular architecture allows flexible deployment options based on user requirements.
Version 2.0 of atlas-mcp-server marks a significant update where the system transitioned from SQLite to Neo4j as its primary database. This change enhances performance, scalability, and graph-based querying capabilities.
Key features include project lifecycle management, real-time collaborative whiteboards, dependency tracking, role-based access control, Neo4j-powered advanced search, bulk operations, and robust error handling mechanisms.
You can install it via npm using `npm install atlas-mcp-server` or clone the repository from GitHub and set up dependencies using `npm install`. Ensure Neo4j is configured either locally via Docker or through Neo4j AuraDB.
Neo4j serves as the core graph database powering relationship management, efficient queries, ACID-compliant transactions, and scalability within atlas-mcp-server.
Yes! Contributions are welcome. Fork the repository, create a feature branch, commit your changes, push them, and submit a Pull Request. For bugs or feature requests, create an issue in the repository.
Yes, atlas-mcp-server is licensed under the Apache License 2.0, making it free and open-source software.
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
At mcpserver.shop, you can browse our MCP Server Directory. The directory is categorized by industry (e.g., finance, healthcare, education), and each server comes with detailed descriptions and tags to help you quickly find the option that suits your needs.
The MCP Server Directory on mcpserver.shop is free to browse. However, some servers are hosted by third-party providers and may involve usage fees. Check the detailed page of each server for specific information.
MCP Servers support a wide range of data sources, including databases, APIs, cloud services, and custom tools. The flexibility of the MCP protocol allows it to connect almost any type of data source to AI models.
MCP Servers are primarily designed for developers, data scientists, and AI app builders. However, mcpserver.shop provides detailed documentation and guides to help users of varying technical levels get started easily.
Yes, MCP is an open-source protocol that encourages community participation and collaboration. For more details or to contribute, visit the official MCP documentation.
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