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GitHub - different-ai/openwork: An open-source alternative to Claude Cowork, powered by OpenCode.

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Articoli Interessanti - This article is part of a series.
Part : This Article
Part : How to Build an Agent - Amp **Introduction** Building an agent, especially one that leverages the power of Amp, involves several key steps. Amp, which stands for Advanced Multi-Purpose Protocol, is a versatile framework designed to enhance the capabilities of agents in various domains. This guide will walk you through the process of creating an agent using Amp, from conceptualization to deployment. **1. Define the Purpose and Scope** Before diving into the technical details, it's crucial to define the purpose and scope of your agent. Ask yourself the following questions: - What specific tasks will the agent perform? - In what environments will the agent operate? - What are the key performance metrics for success? **2. Choose the Right Tools and Technologies** Selecting the appropriate tools and technologies is essential for building a robust agent. For an Amp-based agent, you might need: - **Programming Languages**: Python, Java, or C++ are commonly used. - **Development Frameworks**: TensorFlow, PyTorch, or custom frameworks compatible with Amp. - **Data Sources**: APIs, databases, or real-time data streams. - **Communication Protocols**: HTTP, WebSockets, or other protocols supported by Amp. **3. Design the Agent Architecture** The architecture of your agent will determine its efficiency and scalability. Consider the following components: - **Input Layer**: Handles data ingestion from various sources. - **Processing Layer**: Processes the data using algorithms and models. - **Output Layer**: Delivers the results to the end-users or other systems. - **Feedback Loop**: Allows the agent to learn and improve over time. **4. Develop the Core Functionality** With the architecture in place, start developing the core functionality of your agent. This includes: - **Data Ingestion**: Implementing mechanisms to collect and preprocess data. - **Algorithm Development**: Creating or integrating algorithms that will drive the agent's decision-making. - **Model Training**: Training machine learning models if applicable. - **Integration**: Ensuring seamless integration with other systems and protocols. **5. Implement Amp Protocols** Integrate Amp protocols into your agent to leverage its advanced capabilities. This might involve: - **Protocol Implementation**: Writing code to adhere to Amp standards. - **Communication**: Ensuring the agent can communicate effectively with other Amp-compatible systems. - **Security**: Implementing security measures to protect data and communications. **6. Testing and Validation** Thoroughly test
Part : Everything as Code: How We Manage Our Company In One Monorepo At Kasava, we've embraced the concept of "everything as code" to streamline our operations and ensure consistency across our projects. This approach allows us to manage our entire company within a single monorepo, providing a unified source of truth for all our configurations, infrastructure, and applications. **Why a Monorepo?** A monorepo offers several advantages: 1. **Unified Configuration**: All our settings, from development environments to production, are stored in one place. This makes it easier to maintain consistency and reduces the risk of configuration drift. 2. **Simplified Dependency Management**: With all our code in one repository, managing dependencies becomes more straightforward. We can easily track which versions of libraries and tools are being used across different projects. 3. **Enhanced Collaboration**: A single repository fosters better collaboration among team members. Everyone has access to the same codebase, making it easier to share knowledge and work together on projects. 4. **Consistent Build and Deployment Processes**: By standardizing our build and deployment processes, we ensure that all our applications follow the same best practices. This leads to more reliable and predictable deployments. **Our Monorepo Structure** Our monorepo is organized into several key directories: - **/config**: Contains all configuration files for various environments, including development, staging, and production. - **/infrastructure**: Houses the infrastructure as code (IaC) scripts for provisioning and managing our cloud resources. - **/apps**: Includes all our applications, both internal tools and customer-facing products. - **/lib**: Stores reusable libraries and modules that can be shared across different projects. - **/scripts**: Contains utility scripts for automating various tasks, such as data migrations and backups. **Tools and Technologies** To manage our monorepo effectively, we use a combination of tools and technologies: - **Version Control**: Git is our primary version control system, and we use GitHub for hosting our repositories. - **Continuous Integration/Continuous Deployment (CI/CD)**: We employ Jenkins for automating our build, test, and deployment processes. - **Infrastructure as Code (IaC)**: Terraform is our tool of choice for managing cloud infrastructure. - **Configuration Management**: Ansible is used for configuring and managing our servers and applications. - **Monitoring and Logging**: We use Prometheus and Grafana for monitoring,
Part : Introduction to the MCP Toolbox for Databases The MCP Toolbox for Databases is a comprehensive suite of tools designed to facilitate the management, optimization, and maintenance of databases. This toolbox is tailored to support a wide range of database management systems (DBMS), ensuring compatibility and efficiency across various platforms. Whether you are a database administrator, developer, or analyst, the MCP Toolbox provides a robust set of features to streamline your workflow and enhance productivity. Key Features: 1. **Database Management**: Easily create, modify, and delete databases and tables. The toolbox offers intuitive interfaces and powerful scripting capabilities to manage database schemas and objects efficiently. 2. **Performance Optimization**: Identify and resolve performance bottlenecks with advanced diagnostic tools. The MCP Toolbox includes performance monitoring and tuning features to ensure your databases run smoothly and efficiently. 3. **Backup and Recovery**: Implement reliable backup and recovery solutions to safeguard your data. The toolbox provides automated backup schedules and comprehensive recovery options to protect against data loss. 4. **Security Management**: Enhance database security with robust access control and encryption features. The MCP Toolbox helps you manage user permissions, audit logs, and secure data transmission. 5. **Data Integration**: Seamlessly integrate data from multiple sources and formats. The toolbox supports various data integration techniques, including ETL (Extract, Transform, Load) processes, to consolidate and analyze data effectively. 6. **Reporting and Analytics**: Generate insightful reports and perform in-depth data analysis. The MCP Toolbox offers advanced reporting tools and analytics capabilities to derive actionable insights from your data. 7. **Cross-Platform Compatibility**: Ensure compatibility with multiple DBMS platforms, including popular systems like Oracle, SQL Server, MySQL, and PostgreSQL. The toolbox is designed to work seamlessly across different environments. 8. **User-Friendly Interface**: Benefit from an intuitive and user-friendly interface that simplifies complex database tasks. The MCP Toolbox is designed with ease of use in mind, making it accessible to both novice and experienced users. The MCP Toolbox for Databases is an essential tool for anyone involved in database management. Its comprehensive features and cross-platform compatibility make it a valuable asset for optimizing database performance, ensuring data security, and enhancing overall productivity.
openwork repository preview
#### Source

Type: GitHub Repository Original Link: https://github.com/different-ai/openwork Publication Date: 2026-01-19


Summary
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Introduction
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Imagine you are a financial analyst who needs to analyze various types of documents, including financial reports, emails, and bank transactions, to identify a fraudulent transaction. Each document is in a different format and requires specific tools to be analyzed. Additionally, you need to collaborate with colleagues in different locations, sharing results and updates in real-time. This scenario is common for many knowledge workers, but it can become a logistical and technical nightmare.

This is where OpenWork comes into play. This open-source project, powered by OpenCode, is designed to simplify the workflow of knowledge workers, transforming complex tasks into a clean and guided user experience. OpenWork is not just another interface for developers; it is a solution that makes “agentic” work (i.e., automated and intelligent) accessible and intuitive for everyone.

What It Does
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OpenWork is a native desktop application that leverages the power of OpenCode but presents it in a clean and guided user interface. Here’s how it works: you can choose a workspace, start a run, monitor progress and plan updates, approve permission requests when necessary, and reuse what works thanks to predefined templates and skills.

Think of OpenWork as a virtual assistant that guides you through your workflow. Instead of having to navigate through terminal commands and configuration files, you can focus on your actual work. For example, if you are a financial analyst, you can upload your documents, start an analysis, and receive real-time updates without having to manually intervene at every step.

Why It’s Amazing
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The “wow” factor of OpenWork lies in its ability to make complex work accessible and manageable. It is not just an automation tool; it is a platform that allows you to work smarter, not harder.

Dynamic and Contextual:
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OpenWork is designed to be extensible. You can install OpenCode skills and plugins as modules, allowing you to adapt the platform to your specific needs. For example, if you work in finance, you can install plugins specific to financial data analysis, while a medical researcher might use plugins for genetic data analysis. This makes OpenWork a versatile tool that can grow with your needs.

Real-time Reasoning:
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One of the most powerful features of OpenWork is its ability to provide real-time updates. Thanks to live streaming via SSE (Server-Sent Events), you can monitor the progress of your analyses and receive immediate notifications of any issues or permission requests. This is particularly useful in critical scenarios, such as detecting a fraudulent transaction. Imagine receiving an immediate alert: “Hello, I am your system. The transaction analysis service has detected an anomaly. Do you want to approve access to detailed data for further investigation?”

Auditable and Transparent:
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OpenWork is designed to be auditable, showing exactly what happened, when, and why. This is crucial for transparency and security, especially in regulated sectors such as finance. You can review the entire history of actions performed, understand the decisions made by the system, and intervene if necessary. This level of transparency is a significant step forward compared to traditional tools that often operate as black boxes.

Secure and Controlled:
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Permission management is another strong point of OpenWork. You can configure access to privileged flows and respond to permission requests in a granular way. For example, you can choose to grant access once, always, or completely deny it. This level of control is essential for maintaining the security of your data and processes.

How to Try It
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Trying out OpenWork is simple and straightforward. Here’s how to get started:

  1. Download the Code: You can find the repository on GitHub at https://github.com/different-ai/openwork. Clone the repository to your computer.

  2. Prerequisites: Make sure you have Node.js and pnpm installed. Additionally, you will need the Rust toolchain (for Tauri) and the OpenCode CLI available in your PATH.

  3. Installation: Once the repository is cloned, run pnpm install to install all necessary dependencies.

  4. Launch: To start the desktop application, use the command pnpm dev. If you prefer to try only the web interface, use pnpm dev:web.

  5. Documentation: The main documentation is available in the repository’s README. You will find detailed instructions on how to configure and use OpenWork.

There is no one-click demo, but the setup process is well-documented and supported by the community. If you encounter issues, you can always refer to the discussions on the project’s page for further clarification.

Final Thoughts
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OpenWork represents a significant step forward in how knowledge workers can interact with complex automation tools. Positioning itself within the broader tech ecosystem, OpenWork demonstrates how open-source can revolutionize sectors such as finance, medical research, and much more. Its ability to be extensible, transparent, and secure makes it a valuable tool for anyone working with complex and sensitive data.

In conclusion, OpenWork is not just a technological project; it is a vision of how future work could be more efficient, secure, and accessible. With community support and continuous development, OpenWork has the potential to become a standard for knowledge workers around the world. Try it today and discover how it can transform your workflow.


Use Cases
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  • Private AI Stack: Integration into proprietary pipelines
  • Client Solutions: Implementation for client projects
  • Development Acceleration: Reduction of time-to-market for projects

Third-Party Feedback
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Community Feedback: Users appreciate the initiative but express concerns about file version management and security. Some prefer to wait for further developments before adopting the solution.

Complete Discussion


Resources
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Original Links #


Article recommended and selected by the Human Technology eXcellence team, processed through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2026-01-19 11:00 Original Source: https://github.com/different-ai/openwork

Related Articles #

Articoli Interessanti - This article is part of a series.
Part : This Article
Part : How to Build an Agent - Amp **Introduction** Building an agent, especially one that leverages the power of Amp, involves several key steps. Amp, which stands for Advanced Multi-Purpose Protocol, is a versatile framework designed to enhance the capabilities of agents in various domains. This guide will walk you through the process of creating an agent using Amp, from conceptualization to deployment. **1. Define the Purpose and Scope** Before diving into the technical details, it's crucial to define the purpose and scope of your agent. Ask yourself the following questions: - What specific tasks will the agent perform? - In what environments will the agent operate? - What are the key performance metrics for success? **2. Choose the Right Tools and Technologies** Selecting the appropriate tools and technologies is essential for building a robust agent. For an Amp-based agent, you might need: - **Programming Languages**: Python, Java, or C++ are commonly used. - **Development Frameworks**: TensorFlow, PyTorch, or custom frameworks compatible with Amp. - **Data Sources**: APIs, databases, or real-time data streams. - **Communication Protocols**: HTTP, WebSockets, or other protocols supported by Amp. **3. Design the Agent Architecture** The architecture of your agent will determine its efficiency and scalability. Consider the following components: - **Input Layer**: Handles data ingestion from various sources. - **Processing Layer**: Processes the data using algorithms and models. - **Output Layer**: Delivers the results to the end-users or other systems. - **Feedback Loop**: Allows the agent to learn and improve over time. **4. Develop the Core Functionality** With the architecture in place, start developing the core functionality of your agent. This includes: - **Data Ingestion**: Implementing mechanisms to collect and preprocess data. - **Algorithm Development**: Creating or integrating algorithms that will drive the agent's decision-making. - **Model Training**: Training machine learning models if applicable. - **Integration**: Ensuring seamless integration with other systems and protocols. **5. Implement Amp Protocols** Integrate Amp protocols into your agent to leverage its advanced capabilities. This might involve: - **Protocol Implementation**: Writing code to adhere to Amp standards. - **Communication**: Ensuring the agent can communicate effectively with other Amp-compatible systems. - **Security**: Implementing security measures to protect data and communications. **6. Testing and Validation** Thoroughly test
Part : Everything as Code: How We Manage Our Company In One Monorepo At Kasava, we've embraced the concept of "everything as code" to streamline our operations and ensure consistency across our projects. This approach allows us to manage our entire company within a single monorepo, providing a unified source of truth for all our configurations, infrastructure, and applications. **Why a Monorepo?** A monorepo offers several advantages: 1. **Unified Configuration**: All our settings, from development environments to production, are stored in one place. This makes it easier to maintain consistency and reduces the risk of configuration drift. 2. **Simplified Dependency Management**: With all our code in one repository, managing dependencies becomes more straightforward. We can easily track which versions of libraries and tools are being used across different projects. 3. **Enhanced Collaboration**: A single repository fosters better collaboration among team members. Everyone has access to the same codebase, making it easier to share knowledge and work together on projects. 4. **Consistent Build and Deployment Processes**: By standardizing our build and deployment processes, we ensure that all our applications follow the same best practices. This leads to more reliable and predictable deployments. **Our Monorepo Structure** Our monorepo is organized into several key directories: - **/config**: Contains all configuration files for various environments, including development, staging, and production. - **/infrastructure**: Houses the infrastructure as code (IaC) scripts for provisioning and managing our cloud resources. - **/apps**: Includes all our applications, both internal tools and customer-facing products. - **/lib**: Stores reusable libraries and modules that can be shared across different projects. - **/scripts**: Contains utility scripts for automating various tasks, such as data migrations and backups. **Tools and Technologies** To manage our monorepo effectively, we use a combination of tools and technologies: - **Version Control**: Git is our primary version control system, and we use GitHub for hosting our repositories. - **Continuous Integration/Continuous Deployment (CI/CD)**: We employ Jenkins for automating our build, test, and deployment processes. - **Infrastructure as Code (IaC)**: Terraform is our tool of choice for managing cloud infrastructure. - **Configuration Management**: Ansible is used for configuring and managing our servers and applications. - **Monitoring and Logging**: We use Prometheus and Grafana for monitoring,
Part : Introduction to the MCP Toolbox for Databases The MCP Toolbox for Databases is a comprehensive suite of tools designed to facilitate the management, optimization, and maintenance of databases. This toolbox is tailored to support a wide range of database management systems (DBMS), ensuring compatibility and efficiency across various platforms. Whether you are a database administrator, developer, or analyst, the MCP Toolbox provides a robust set of features to streamline your workflow and enhance productivity. Key Features: 1. **Database Management**: Easily create, modify, and delete databases and tables. The toolbox offers intuitive interfaces and powerful scripting capabilities to manage database schemas and objects efficiently. 2. **Performance Optimization**: Identify and resolve performance bottlenecks with advanced diagnostic tools. The MCP Toolbox includes performance monitoring and tuning features to ensure your databases run smoothly and efficiently. 3. **Backup and Recovery**: Implement reliable backup and recovery solutions to safeguard your data. The toolbox provides automated backup schedules and comprehensive recovery options to protect against data loss. 4. **Security Management**: Enhance database security with robust access control and encryption features. The MCP Toolbox helps you manage user permissions, audit logs, and secure data transmission. 5. **Data Integration**: Seamlessly integrate data from multiple sources and formats. The toolbox supports various data integration techniques, including ETL (Extract, Transform, Load) processes, to consolidate and analyze data effectively. 6. **Reporting and Analytics**: Generate insightful reports and perform in-depth data analysis. The MCP Toolbox offers advanced reporting tools and analytics capabilities to derive actionable insights from your data. 7. **Cross-Platform Compatibility**: Ensure compatibility with multiple DBMS platforms, including popular systems like Oracle, SQL Server, MySQL, and PostgreSQL. The toolbox is designed to work seamlessly across different environments. 8. **User-Friendly Interface**: Benefit from an intuitive and user-friendly interface that simplifies complex database tasks. The MCP Toolbox is designed with ease of use in mind, making it accessible to both novice and experienced users. The MCP Toolbox for Databases is an essential tool for anyone involved in database management. Its comprehensive features and cross-platform compatibility make it a valuable asset for optimizing database performance, ensuring data security, and enhancing overall productivity.