The Cursor10x MCP is a persistent multi-dimensional memory system for Cursor that enhances AI assistants with conversation context, project history, and code relationships across sessions.
Configuration
View docs{
"mcpServers": {
"aiurda-cursor10x-mcp": {
"command": "npx",
"args": [
"cursor10x-mcp"
],
"env": {
"TURSO_AUTH_TOKEN": "YOUR_TURSO_AUTH_TOKEN",
"TURSO_DATABASE_URL": "YOUR_TURSO_DATABASE_URL"
}
}
}
}DevContext MCP Server provides a dedicated, autonomous memory context system that helps AI assistants stay aware of your project across sessions. It organizes memory into short-term, long-term, episodic, and semantic layers, enabling fast, relevance-based retrieval and seamless code-aware interactions for development workflows.
You operate DevContext MCP Server through an MCP client that talks to the local stdio server. Start the server locally, then run commands from your project to initialize conversations, store and retrieve memory, and manage context for ongoing development tasks.
Initializes a conversation by storing the user message, generating a banner, and retrieving context in one operation, reducing setup steps at the start of conversations.
Ends a conversation by storing the assistant's final message, recording a milestone, and logging an episode in episodic memory.
Checks the health of the memory system and its database connection.
Retrieves detailed statistics about the memory system.
Retrieves a unified context from all memory subsystems to inform the current interaction.
Stores a user message in short-term memory with optional importance and metadata.
Stores an assistant message in short-term memory with optional importance and metadata.
Tracks an active file being accessed or modified by the user.
Retrieves recent messages from short-term memory with optional filters.
Retrieves currently active files from short-term memory.
Stores a project milestone in long-term memory.
Stores a project decision in long-term memory.
Stores a project requirement in long-term memory.
Records an episodic memory item describing an action within the project.
Retrieves recent episodes from episodic memory.
Unified tool for storing and querying vector embeddings for semantic search across memory.