All AI tools share memory! MCP protocol allows knowledge base to evolve into a 'living' intelligent hub

In our daily work, we are increasingly accustomed to combining multiple AI tools to improve efficiency. However, a common problem is that these tools often work independently and cannot share "memory", which interrupts our workflow.

Imagine a scenario like this:

1. You first consulted a large number of the latest policy documents and market analysis reports on a certain industry in the Tencent IMA knowledge base , and gained a preliminary understanding of the project background and key data.
2. Next, you want an AI writing assistant (such as Gemini or Wenxinyiyan) to help you draft a first draft of a project proposal based on this information. At this time, you have to manually copy and paste key information, or re-describe the core insights you gained in IMA to the writing AI.
3. After the first draft is completed, you may need Doubao or other AI drawing tools to generate a schematic diagram based on a core idea or business process in the proposal. Again, you need to explain your needs and related background to the drawing AI again.
4. Finally, if the proposal requires a short demo video, you might turn to an AI video generation tool like Dream , which still knows nothing about all the contextual information you have accumulated from IMA, writing AI, and drawing AI.

In such a typical  workflow of "information research -> manuscript writing -> visual presentation -> dynamic demonstration"  , each step of switching AI tools may be accompanied by a large amount of repeated information input and contextual explanation. This "memory gap" between AI tools undoubtedly greatly affects our work efficiency and creative fluency.

The good news is that an open source tool called  OpenMemory MCP  is dedicated to solving this pain point. Its core goal, in simple terms, is to enable your various AI tools to access a shared, persistent "memory center."

1. OpenMemory MCP: Let AI have a "shared brain hard drive"

OpenMemory MCP is a product powered by mem0ai and built on the Open Model Context Protocol (MCP)  . It provides private, persistent memory services for MCP-compatible AI clients such as Cursor, Claude Desktop, Windsurf, Cline, etc.

According to the official introduction, its main features and advantages can be summarized as follows:

• Solve the "amnesia" pain point of AI tools:  It provides a persistent memory layer for AI tools, so that the conversation context information can be continued between different tools and different conversations, and no longer "forget after the conversation".
• Cross-tool context sharing:  This is its core highlight. You can use Claude to plan a project roadmap, and then seamlessly switch to Cursor to perform specific coding tasks. The two tools can share and utilize the same context information to ensure the consistency of the workflow.
• Based on the MCP protocol, 100% local operation:  The MCP protocol is designed to standardize the exchange of contextual information between AI models. OpenMemory MCP supports running completely in a local environment, so users can better control their data, ensure information security, and are not restricted by specific cloud service providers.
• Standardized memory operations and cross-platform support:  Provides a unified memory operation interface (such as adding, searching, listing, and deleting memories), and supports running on mainstream desktop and mobile operating systems, making it easier for users to synchronize and manage memories across different devices and tools.

Simply put, OpenMemory MCP attempts to build a bridge for originally isolated AI applications through an open protocol, allowing them to share a "long-term memory library" and work together more intelligently.

2. When “shared memory” meets AI knowledge base: sparks of collision

After understanding the concept of OpenMemory MCP, we naturally wonder: If this "shared memory among all AI tools" capability is combined with the AI ​​knowledge base (such as Tencent IMA, etc.) that we increasingly rely on in our daily work and study, what changes will it bring?

I think there are at least two core positive effects:

1. AI knowledge base: upgraded from “information island” to “universal memory center”

The current AI knowledge base is often more like an independent "information storage and retrieval system". The emergence of OpenMemory MCP is expected to make the AI ​​knowledge base play a more core role - becoming the "common background knowledge source" and "long-term memory library" of all AI tools in the entire MCP ecosystem.

• Imagine this:
• A consulting company has deposited its accumulated industry reports, policy interpretations, project cases, methodologies, etc. in AI knowledge base A.
• At the same time, in daily work, consultants will use AI writing assistant B to write plans, AI data analysis tool C to process charts, and AI project management tool D to follow up on progress.
• Through the MCP protocol, when performing tasks, tools B, C, and D can intelligently retrieve relevant background information, data, templates, or historical experience from knowledge base A as context, without the need for consultants to manually switch and copy and paste between multiple systems.
• For example, when the AI ​​code assistant writes a risk control model for a specific financial scenario, it can automatically obtain the latest regulatory regulations and risk point prompts from the company's internal "Financial Compliance AI Knowledge Base" as contextual references.

This combination makes the AI ​​knowledge base no longer just an object of passive query, but can actively provide deep and structured "memory support" for various AI applications.

2. Implementation of a “Living” Knowledge Base: Bidirectional Memory Flow and Continuous Evolution

Furthermore, OpenMemory MCP emphasizes a readable and writable shared memory layer. This means that information flow can be bidirectional:

• Knowledge base empowers AI tools:  AI tools obtain context from the knowledge base.
• AI tools feed back to the knowledge base:  When users use various AI tools to complete specific tasks (such as analyzing data, writing reports, and communicating with customers), new insights, key decisions, project experiences, and even user corrections and feedback on AI outputs can theoretically be recorded in a structured manner through the MCP protocol and have the opportunity to flow back or be associated with the AI ​​knowledge base.

In this way, the AI ​​knowledge base has truly "come alive". It is no longer a static pile of data, but can continuously absorb new "experiences" and "memories" through continuous "interaction" with users and various AI tools, thereby achieving dynamic iteration and self-optimization, becoming more and more intelligent and closer to actual business needs.

For knowledge-intensive industries such as consulting, R&D, and education, the value of this "live" knowledge base that can be shared across tools and continuously evolve is self-evident. It can greatly improve the efficiency of knowledge reuse, accelerate the inheritance of experience, and lay a solid foundation for higher-level intelligent decision support.

Conclusion: Openness and connectivity: the future of AI tool collaboration

OpenMemory MCP and the MCP protocol behind it paint a picture of a future where AI tools evolve from "working independently" to "efficient collaboration". Although it is still in its early stages and the tool ecosystem compatible with MCP is still under development, the concept of "open shared memory" it represents undoubtedly points out a key bottleneck in the current AI application experience.

For AI knowledge bases, this is both an opportunity and a revelation. In the future, the development direction of AI knowledge bases may also need to embrace open standards and interoperability to better integrate into the next generation of AI-driven workflows and unleash their full potential as the "core of intelligence."

Let’s imagine this: when all your AI tools can truly share memories and collaborate seamlessly, what earth-shaking changes will occur in the way we work?