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Byterover MCP Server

Powering Coding Agent Collaboration with Shared Memory

Give [Cursor](https://cursor.sh/), [Windsurf](https://codeium.com/windsurf), [Cline](https://cline.bot/), and other AI-powered coding agents the shared long term memory so that they can perform the task well together with the relavant context with this [Model Context Protocol](https://modelcontextprotocol.io/introduction) server. When Cursor has the knowledge about the codebase; experiences in the past about how it has solved the projects's issues with human it's **way** better and cost effective then re-entering the reasoning loop again

See quickstart instructions →

## How it works 1. Open your IDE's chat (e.g. agent mode in Cursor). 2. Let's Agent know how they gonna use the external memories (cursor rules, etc..) 3. Cursor will retrieve and store the relavant memories while perform the tasks ## Getting Started Many code editors and other AI clients use a configuration file to manage MCP servers. The `byterover-mcp` server can be configured by adding the following to your configuration file. > NOTE: You will need to create the access token to use this server. Instructions on how to create a Byterover API access token can be found [here](https://www.byterover.dev/docs/get-started). ### MacOS / Linux ```json { "mcpServers": { "Byterover Memory MCP": { "command": "npx", "args": [ "-y", "byterover-mcp", "--byterover-public-api-key=YOUR-PUBLIC-KEY", "--user-id=YOUR-NAME", "--llm-key-name=YOUR-LLM-KEY-NAME", "--model=YOUR-LLM-MODEL-NAME" ] } } } ``` ### Windows ```json { "mcpServers": { "Byterover Memory MCP": { "command": "cmd", "args": [ "/c", "npx", "-y", "byterover-mcp", "--byterover-public-api-key=YOUR-PUBLIC-KEY", "--user-id=YOUR-NAME", "--llm-key-name=YOUR-LLM-KEY-NAME", "--model=YOUR-LLM-MODEL-NAME" ] } } } ``` If you need more information about Byterover see the [Byterover docs](https://www.byterover.dev).2a:T54c,## What is Byterover MCP Server? Byterover MCP Server is a platform designed to enhance collaboration among AI-powered coding agents by providing them with shared long-term memory, allowing them to perform tasks more effectively with relevant context. ## How to use Byterover MCP Server? To use the Byterover MCP Server, you need to configure it in your code editor's configuration file and create an access token. Follow the quickstart instructions provided in the documentation to set it up. ## Key features of Byterover MCP Server? - Enables shared long-term memory for coding agents. - Integrates with various AI-powered coding tools like Cursor, Windsurf, and Cline. - Provides a Model Context Protocol for better task performance. ## Use cases of Byterover MCP Server? 1. Enhancing collaboration between multiple AI coding agents on a project. 2. Improving task performance by utilizi

Byterover MCP Server

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