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Sugar

Sugar is an autonomous execution layer designed for AI programming agents, providing task queue management, 24/7 continuous operation, and a persistent memory system, supporting integration with mainstream AI coding tools such as Claude Code and OpenCode.
Knowledge management and memoryDeveloper tools#AI programming agent#Task automation#Memory system#Code execution.Python
2.5 points
4.0K
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Overview

Installation

Tools List

Content Details

Alternatives

What is Sugar MCP Server?

Sugar MCP Server is the core component of the Sugar AI assistant platform. It provides project memory and task management functions for AI assistants such as Claude Code and Goose through the Model Context Protocol (MCP) standard. This server allows AI to access and update the project's long - term memory, including technical decisions, development preferences, error patterns, etc., to achieve true cross - session collaboration.

How to use Sugar MCP Server?

Using Sugar MCP Server is very simple: First, make sure the Sugar CLI is installed, and then configure the MCP server in your AI assistant (such as Claude Code). After configuration, the AI assistant can automatically access project memory, obtain relevant context during coding, and create and manage tasks.

Use cases

Sugar MCP Server is particularly suitable for software development projects that require long - term collaboration. When multiple developers or AI assistants work on the same project at different times, it ensures the consistency of technical decisions and development patterns. It is also suitable for complex projects where a large number of architectural decisions and best practices need to be remembered.

Main features

Project memory access
AI assistants can read the project's long - term memory, including technical decisions, development preferences, error patterns, etc., to ensure the correct context during coding.
Task delegation
Create Sugar tasks directly in AI conversations, allowing Sugar to handle them automatically in the background, achieving seamless task handover.
Automatic context injection
Automatically inject relevant memories into AI conversations based on the current work content, without manual search.
Multi - AI assistant support
Supports multiple AI assistants such as Claude Code, OpenCode, and Goose simultaneously, providing a unified memory interface.
Semantic search
Search for relevant memories based on semantic similarity rather than simple keyword matching, providing more accurate context.
Advantages
๐Ÿš€ Significantly reduce repeated explanations: AI assistants automatically obtain project historical decisions, reducing repeated communication
๐Ÿ’พ Save a large number of tokens: Memories are compressed and stored, saving approximately 89% of token usage in actual projects
๐Ÿ”„ Cross - session consistency: Ensure that different AI assistants maintain consistent decisions when handling the same project at different times
โšก Seamless integration: Natively integrated with mainstream AI assistants (Claude Code, OpenCode, etc.)
๐Ÿ”’ Project isolation: Each project has an independent memory library to avoid information confusion
Limitations
๐Ÿ“š Requires initial configuration: The MCP server needs to be configured for the first use
๐Ÿ”„ Depends on AI assistant support: AI assistants need to support the MCP protocol
๐Ÿ’พ Requires local storage: Memories are stored in the project's local.sugar/ directory
๐Ÿ”ง Technical threshold: Non - technical users may need help with the initial setup

How to use

Install Sugar CLI
Install Sugar globally using pipx to ensure it can be used in any project.
Initialize the project
Initialize Sugar in the project directory to create local configuration and database.
Configure the AI assistant
Configure the Sugar MCP server according to the AI assistant you are using. Here are the configuration methods for different assistants.
Start using
Restart the AI assistant. Now it can access project memory and create Sugar tasks.

Usage examples

Case 1: A new developer joins the project
When a new developer (or AI assistant) joins an existing project, Sugar MCP Server can automatically provide important project decisions and patterns, reducing the learning cost.
Case 2: Handling repeated errors
When encountering repeated errors, Sugar can remember error patterns and solutions to help solve problems quickly.
Case 3: Delegating background tasks
During the main development work, secondary tasks can be delegated to Sugar to handle, keeping the workflow uninterrupted.

Frequently Asked Questions

Which AI assistants does Sugar MCP Server support?
Where is the project memory stored? Is it secure?
How to manage or delete old memories?
Can multiple AI assistants access the same memory simultaneously?
Will the memory affect the performance of the AI assistant?

Related resources

Sugar official documentation
Complete documentation for the Sugar platform, including installation, configuration, and advanced features
MCP protocol specification
Official specification of the Model Context Protocol to understand how MCP works
Claude Code documentation
Official documentation and MCP configuration guide for Claude Code
OpenCode GitHub repository
OpenCode open - source project to understand its MCP integration capabilities
Sugar configuration examples
Various configuration and usage examples, including MCP server configuration

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "sugar": {
      "type": "stdio",
      "command": "sugar",
      "args": ["mcp", "memory"]
    }
  }
}

{
  "mcpServers": {
    "sugar": {
      "command": "npx",
      "args": ["-y", "sugarai-mcp"],
      "env": {
        "SUGAR_PROJECT_ROOT": "/path/to/your/project"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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