Integrate Basic Memory with Zed Editor for persistent knowledge using Markdown and Large Language Models
The Basic Memory MCP Server extension connects AI applications like Claude Desktop, Continue, and Cursor through the Model Context Protocol (MCP). This allows these AI tools to access and integrate with persistent knowledge stored in markdown files using Basic Memory. By leveraging MCP, developers can enhance their AI workflows by seamlessly embedding external data sources into their applications.
The Basic Memory MCP Server implements the MCP protocol to enable two-way communication between AI clients and a local or remote context server hosted by Basic Memory. Key features include:
Persistent Knowledge Storage: The extension integrates with Basic Memory, enabling users to store detailed notes, research findings, and other documents in Markdown format locally on their computers.
Natural Language Understanding (NLU): MCP allows AI applications to understand and respond to natural language prompts to retrieve, create, and modify content stored in Basic Memory.
Version Control: Supports versioning for notes and data, ensuring that changes are tracked and can be reverted if needed.
With the introduction of MCP tools support in Zed Editor, this extension significantly enhances the capabilities of AI applications by providing a robust API for accessing contextual information securely. This interoperability is crucial for developers looking to build comprehensive and context-aware AIs.
The Basic Memory MCP Server leverages the Model Context Protocol (MCP) to implement a seamless integration between Zed Editor's Assistant and Basic Memory's persistent knowledge storage system. The architecture can be visualized as follows:
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server - Basic Memory]
C --> D[Data Source/Tool (Markdown Files)]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
MCP Client: Installed in Zed Editor, this client sends and receives requests via the MCP protocol.
MCP Protocol: The standardized communication mechanism used to exchange data between the client and server.
MCP Server (Basic Memory): Serves as the backend for storing and retrieving contextually relevant information.
This architecture ensures that AI applications can access, modify, and use knowledge stored in Basic Memory without any modifications to their internal codebases. The protocol flow is designed to be flexible and modular, allowing for future expansion and extension of supported clients and tools.
To get started, ensure that you have Python 3.12+ installed along with the necessary packages:
pip install uv
uv tool install basic-memory
This step installs both uv
(a universal package manager for Zed Editor extensions) and basic-memory
, which serves as the context server.
Navigate to Zed > Extensions or use the command palette to search for "extensions". Once installed, configure the Basic Memory MCP Server:
{
"context_servers": {
"mcp-server-basic-memory": {
"settings": {
"project": "optional-project-name"
}
}
}
}
The project
setting is optional. If specified, the project will use the named project for storing and accessing notes; otherwise, it defaults to the initial project configuration.
Modify your Zed Editor settings by adding the following JSON snippet under "context_servers":
{
"mcpServers": {
"basic-memory": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-basic-memory"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
Note Creation and Management:
Knowledge Sharing and Collaboration:
The Basic Memory MCP Server is fully compatible with major MCPC clients, including:
Claude Desktop: Full support for all features such as note creation, editing, and searching.
Continue: Support for data exchange and integration, with some limitations due to its current development stage.
Cursor: Limited compatibility since the tool does not yet support MCP interactions. However, Basic Memory provides a standard interface that can be integrated seamlessly once Cursor adds MCP support.
The following table outlines the current status of MCPC client integration with the Basic Memory MCP Server:
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
This matrix helps developers understand the current state of compatibility and plan accordingly for future integrations.
API Key Protection: The API_KEY
environment variable ensures secure access to the Basic Memory context server.
Data Encryption: All data transmitted between the AI application and Basic Memory is encrypted using standard security protocols.
Below is an example of advanced configuration code for setting up API keys within the context of MCP servers:
{
"context_servers": {
"basic-memory": {
"settings": {
"project": "default-project",
"api_key": "your-safe-api-key-here"
}
}
}
}
To install, run pip install uv
and uv tool install basic-memory
. Then navigate to Zed Editor's extensions and add "mcp-server-basic-memory".
Yes, it is designed to be compatible with other MCPC clients such as Continue and Cursor.
Projects allow you to organize your knowledge bases for different projects or purposes. Use named projects to separate contexts for various workflows.
Store your API key using environment variables or secure vaults, especially when running on shared machines.
Basic Memory provides persistent storage and easy access to contextual information, enhancing the efficiency of data-driven decisions in AI applications.
Contributions are welcome! If you're interested in contributing, please review our contribution guidelines for details on how to get involved. Your help can significantly enhance the functionality and usability of Basic Memory as an MCP server.
For more detailed information about MCPC-related projects, explore:
By integrating the Basic Memory MCP Server into your AI workflows, you can enhance collaboration, data management, and productivity. This solution provides a robust foundation for developers looking to build sophisticated AI applications with persistent context-aware knowledge integration.
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