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PMB is a local-first memory system that empowers AI coding agents like Claude Code and Codex to remember decisions and lessons across sessions by storing data in a single SQLite file on your disk. Ideal for developers who need offline, fast, and private AI memory without relying on cloud services or API keys.
Description
PMB gives Claude Code, Cursor, Codex and Zed persistent project memory through MCP. It stores decisions, lessons, goals, recent work, project facts and docs in one SQLite workspace on your disk. No cloud, no API keys, no LLM call on the read path. It is open source, offline-first, inspectable/exportable, with a local dashboard and honest impact tracking so you can see which memories actually help.
Detailed Description
PMB is a specialized local-first memory solution designed to enhance the capabilities of AI coding agents such as Claude Code, Cursor, Codex, and Zed. Its core purpose is to provide these AI agents with persistent memory by storing decisions, lessons, and project-related facts in a single SQLite file directly on the user's disk. This approach eliminates the need for cloud storage or API keys, enabling offline functionality and giving users full control over their data. By integrating memory locally, PMB allows AI agents to recall relevant information quickly and maintain continuity across sessions, which is critical for complex coding tasks and long-term projects. One of the standout features of PMB is its local-first architecture, which means all memory data is stored on the user's device in a compact SQLite database. This ensures data privacy and security, as no information is sent to external servers or cloud services. The memory recall speed is optimized to around 35 milliseconds, allowing AI agents to access past decisions and lessons almost instantaneously. PMB supports multiple popular AI coding agents, including Claude Code, Cursor, Codex, and Zed, making it a versatile choice for developers working with different AI tools. Additionally, PMB is built to integrate seamlessly with the MCP-native architecture, which facilitates efficient communication and data exchange between the memory system and AI agents. Installation and setup are straightforward, with PMB available as an open-source package under the Apache 2.0 license. Users can easily install it via pip, making it accessible for Python developers and those familiar with standard package management. The open-source nature of PMB encourages community contributions and transparency, allowing developers to customize or extend its capabilities to fit specific project needs. PMB is particularly well-suited for AI developers, software engineers, and teams who rely on AI coding assistants for complex programming tasks. It is ideal for scenarios where maintaining context and continuity over multiple sessions is crucial, such as long-term software development projects, collaborative coding environments, or learning systems that benefit from accumulated knowledge. By providing a reliable and fast memory layer, PMB helps AI agents deliver more coherent and context-aware assistance, improving productivity and reducing repetitive explanations or re-training. Regarding pricing, PMB is an open-source tool, which means it is free to use without subscription fees or licensing costs. This makes it an attractive option for individual developers, startups, and organizations looking to enhance their AI coding workflows without incurring additional expenses. Compared to cloud-based memory solutions or API-dependent services, PMB offers significant advantages in privacy, offline availability, and control. Many alternatives require internet connectivity and expose data to third-party servers, which can be a concern for sensitive projects. However, PMB’s local-first design means users retain full ownership of their data and can operate in environments with limited or no internet access. Despite its strengths, PMB may have some limitations. Since it relies on local storage, the memory capacity is constrained by the user's hardware and disk space. Additionally, while it supports several popular AI coding agents, integration with other or newer agents may require additional development effort. Users should also consider that managing local memory files involves responsibility for backups and data integrity, unlike cloud solutions that often provide automated redundancy. In summary, PMB is a powerful, privacy-focused memory solution that significantly enhances AI coding agents by providing fast, local, and persistent memory. Its ease of installation, open-source license, and offline capabilities make it an excellent choice for developers seeking to improve AI-assisted coding workflows while maintaining full control over their data.
Tool Features
- Local-first memory stored in one SQLite file on your disk
- Works offline with no API keys or cloud required
- Supports AI coding agents like Claude Code, Cursor, Codex, and Zed
- Enables fast recall of decisions, lessons, and project facts (~35ms)
- Integrates with MCP-native architecture
- Open source under Apache 2.0 license
- Easy installation via pip
Description
✦
PMB is a local-first memory system that empowers AI coding agents like Claude Code and Codex to remember decisions and lessons across sessions by storing data in a single SQLite file on your disk. Ideal for developers who need offline, fast, and private AI memory without relying on cloud services or API keys.
PMB gives Claude Code, Cursor, Codex and Zed persistent project memory through MCP. It stores decisions, lessons, goals, recent work, project facts and docs in one SQLite workspace on your disk. No cloud, no API keys, no LLM call on the read path. It is open source, offline-first, inspectable/exportable, with a local dashboard and honest impact tracking so you can see which memories actually help.
Detailed Description
PMB is a specialized local-first memory solution designed to enhance the capabilities of AI coding agents such as Claude Code, Cursor, Codex, and Zed. Its core purpose is to provide these AI agents with persistent memory by storing decisions, lessons, and project-related facts in a single SQLite file directly on the user's disk. This approach eliminates the need for cloud storage or API keys, enabling offline functionality and giving users full control over their data. By integrating memory locally, PMB allows AI agents to recall relevant information quickly and maintain continuity across sessions, which is critical for complex coding tasks and long-term projects. One of the standout features of PMB is its local-first architecture, which means all memory data is stored on the user's device in a compact SQLite database. This ensures data privacy and security, as no information is sent to external servers or cloud services. The memory recall speed is optimized to around 35 milliseconds, allowing AI agents to access past decisions and lessons almost instantaneously. PMB supports multiple popular AI coding agents, including Claude Code, Cursor, Codex, and Zed, making it a versatile choice for developers working with different AI tools. Additionally, PMB is built to integrate seamlessly with the MCP-native architecture, which facilitates efficient communication and data exchange between the memory system and AI agents. Installation and setup are straightforward, with PMB available as an open-source package under the Apache 2.0 license. Users can easily install it via pip, making it accessible for Python developers and those familiar with standard package management. The open-source nature of PMB encourages community contributions and transparency, allowing developers to customize or extend its capabilities to fit specific project needs. PMB is particularly well-suited for AI developers, software engineers, and teams who rely on AI coding assistants for complex programming tasks. It is ideal for scenarios where maintaining context and continuity over multiple sessions is crucial, such as long-term software development projects, collaborative coding environments, or learning systems that benefit from accumulated knowledge. By providing a reliable and fast memory layer, PMB helps AI agents deliver more coherent and context-aware assistance, improving productivity and reducing repetitive explanations or re-training. Regarding pricing, PMB is an open-source tool, which means it is free to use without subscription fees or licensing costs. This makes it an attractive option for individual developers, startups, and organizations looking to enhance their AI coding workflows without incurring additional expenses. Compared to cloud-based memory solutions or API-dependent services, PMB offers significant advantages in privacy, offline availability, and control. Many alternatives require internet connectivity and expose data to third-party servers, which can be a concern for sensitive projects. However, PMB’s local-first design means users retain full ownership of their data and can operate in environments with limited or no internet access. Despite its strengths, PMB may have some limitations. Since it relies on local storage, the memory capacity is constrained by the user's hardware and disk space. Additionally, while it supports several popular AI coding agents, integration with other or newer agents may require additional development effort. Users should also consider that managing local memory files involves responsibility for backups and data integrity, unlike cloud solutions that often provide automated redundancy. In summary, PMB is a powerful, privacy-focused memory solution that significantly enhances AI coding agents by providing fast, local, and persistent memory. Its ease of installation, open-source license, and offline capabilities make it an excellent choice for developers seeking to improve AI-assisted coding workflows while maintaining full control over their data.
Frequently Asked Questions
What is PMB?
PMB is a local-first memory solution designed for AI coding agents, enabling them to store and recall decisions, lessons, and project facts in a single SQLite file on your disk. This allows AI agents to maintain continuity across sessions without relying on cloud storage or API keys.
How much does PMB cost?
PMB is open source and free to use under the Apache 2.0 license, with no subscription fees or licensing costs.
Who is PMB best for?
PMB is best suited for AI developers, software engineers, and teams using AI coding assistants who need persistent, fast, and private memory to improve coding workflows, especially in offline or privacy-sensitive environments.
What are the main features of PMB?
Key features include local-first memory stored in a single SQLite file, offline operation without API keys or cloud dependency, support for AI coding agents like Claude Code, Cursor, Codex, and Zed, fast recall times (~35ms), integration with MCP-native architecture, open-source licensing, and easy installation via pip.
Does PMB offer a free trial?
Since PMB is an open-source tool available for free, there is no need for a free trial; users can install and use it immediately without cost.
What integrations does PMB support?
PMB supports integration with AI coding agents such as Claude Code, Cursor, Codex, and Zed, and it is designed to work seamlessly with the MCP-native architecture.
How does PMB work?
PMB stores AI agents' memory data—decisions, lessons, and project facts—in a local SQLite file on your disk. This local-first approach allows AI agents to quickly recall relevant information offline, enhancing their ability to maintain context and continuity across sessions without relying on cloud services or API keys.
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