๐ DevContext - The Next Evolution in AI Development Context
DevContext is a revolutionary tool that takes AI development to new heights. It offers a continuous, project - centric context awareness, enabling developers to have more productive and contextually aware assistance.
๐ Cursor10x is now DevContext ๐
Cursor10x has evolved into DevContext - A more powerful, dedicated context system for developers
| Feature |
Description |
| ๐ง Project - Centric |
One database per project |
| ๐ Relationship Graphs |
Intelligent code connections |
| โก High Performance |
Minimal resource needs |
๐ฅ DevContext takes AI development to the next level ๐ฅ
- ๐ Continuous Context Awareness: Sophisticated retrieval methods focusing on what matters
- ๐ Structured Metadata: From repository structure down to individual functions
- ๐ง Adaptive Learning: Continuously learns from and adapts to your development patterns
- ๐ค Completely Autonomous: Self - managing context system that works in the background
- ๐ External Documentation: Automatically retrieves and integrates relevant documentation
- ๐ Workflow Integration: Seamless task management workflow built - in
๐ Be on the lookout ๐
The DevContext Project Generator is launching in the next couple days and will create a COMPLETE set up for your project to literally 10x your development workflow.
Visit DevContext Repository
DevContext is a cutting - edge Model Context Protocol (MCP) server providing developers with continuous, project - centric context awareness that understands your codebase at a deeper level.
๐ Quick Start
The Cursor10x Memory System creates a persistent memory layer for AI assistants (specifically Claude), enabling them to retain and recall various information such as recent messages, active files, project milestones, and more. This memory system bridges the gap between stateless AI interactions and continuous development workflows, allowing for more productive and contextually aware assistance.
โจ Features
- Persistent Context: Maintains conversation and project context across multiple sessions
- Importance - Based Storage: Prioritizes information based on configurable importance levels
- Multi - Dimensional Memory: Combines short - term, long - term, episodic, and semantic memory systems
- Comprehensive Retrieval: Provides unified context from all memory subsystems
- Health Monitoring: Includes built - in diagnostics and status reporting
- Banner Generation: Creates informative context banners for conversation starts
- Database Persistence: Stores all memory data in Turso database with automatic schema creation
- Vector Embeddings: Creates numerical representations of text and code for semantic search
- Advanced Vector Storage: Utilizes Turso's F32_BLOB and vector functions for efficient embedding storage
- ANN Search: Supports Approximate Nearest Neighbor search for fast similarity matching
- Code Indexing: Automatically detects and indexes code structures (functions, classes, variables)
- Semantic Search: Finds related content based on meaning rather than exact text matches
- Relevance Scoring: Ranks context items by relevance to the current query
- Code Structure Detection: Identifies and extracts code components across multiple languages
- Auto - Embedding Generation: Automatically creates vector embeddings for indexed content
- Cross - Reference Retrieval: Finds related code across different files and components
๐ฆ Installation
Prerequisites
- Node.js 18 or higher
- npm or yarn package manager
- Turso database account
Setup Steps
- Configure Turso Database:
curl -sSfL https://get.turso.tech/install.sh | bash
turso auth login
turso db create cursor10x - mcp
turso db show cursor10x - mcp --url
turso db tokens create cursor10x - mcp
Or you can visit Turso and sign up and proceed to create the database and get proper credentials. The free plan will more than cover your project memory.
- Configure Cursor MCP:
Update .cursor/mcp.json in your project directory with the database url and turso auth token:
{
"mcpServers": {
"cursor10x - mcp": {
"command": "npx",
"args": ["cursor10x - mcp"],
"enabled": true,
"env": {
"TURSO_DATABASE_URL": "your - turso - database - url",
"TURSO_AUTH_TOKEN": "your - turso - auth - token"
}
}
}
}
๐ป Usage Examples
Basic Usage
const result = await mcp_cursor10x_initConversation({
content: "I need to implement a login system for my app",
importance: "medium",
});
Advanced Usage
const result = await mcp_cursor10x_endConversation({
content:
"I've implemented the authentication system with JWT tokens as requested",
milestone_title: "Authentication Implementation",
milestone_description:
"Implemented secure JWT - based authentication with refresh tokens",
importance: "high",
});
๐ Documentation
System Tools
mcp_cursor10x_initConversation
Initializes a conversation by storing the user message, generating a banner, and retrieving context in one operation. This unified tool replaces the need for separate generateBanner, getComprehensiveContext, and storeUserMessage calls at the beginning of each conversation.
Parameters:
content (string, required): Content of the user messageimportance (string, optional): Importance level ("low", "medium", "high", "critical"), defaults to "low"metadata (object, optional): Additional metadata for the message
Returns:
- Object with two sections:
display: Contains the banner to be shown to the userinternal: Contains the comprehensive context for the agent's use
mcp_cursor10x_endConversation
Ends a conversation by combining multiple operations in one call: storing the assistant's final message, recording a milestone for what was accomplished, and logging an episode in the episodic memory. This unified tool replaces the need for separate storeAssistantMessage, storeMilestone, and recordEpisode calls at the end of each conversation.
Parameters:
content (string, required): Content of the assistant's final messagemilestone_title (string, required): Title of the milestone to recordmilestone_description (string, required): Description of what was accomplishedimportance (string, optional): Importance level ("low", "medium", "high", "critical"), defaults to "medium"metadata (object, optional): Additional metadata for all records
Returns:
- Object with status and results of each operation
mcp_cursor10x_checkHealth
Checks the health of the memory system and its database connection.
Parameters:
Returns:
- Object with health status and diagnostics
mcp_cursor10x_getMemoryStats
Retrieves detailed statistics about the memory system.
Parameters:
Returns:
- Object with comprehensive memory statistics
mcp_cursor10x_getComprehensiveContext
Retrieves a unified context from all memory subsystems, combining short - term, long - term, and episodic memory.
Parameters:
Returns:
- Object with consolidated context from all memory systems
Short - Term Memory Tools
mcp_cursor10x_storeUserMessage
Stores a user message in the short - term memory system.
Parameters:
content (string, required): Content of the messageimportance (string, optional): Importance level ("low", "medium", "high", "critical"), defaults to "low"metadata (object, optional): Additional metadata for the message
Returns:
- Object with status and timestamp
mcp_cursor10x_storeAssistantMessage
Stores an assistant message in the short - term memory system.
Parameters:
content (string, required): Content of the messageimportance (string, optional): Importance level ("low", "medium", "high", "critical"), defaults to "low"metadata (object, optional): Additional metadata for the message
Returns:
- Object with status and timestamp
mcp_cursor10x_trackActiveFile
Tracks an active file being accessed or modified by the user.
Parameters:
filename (string, required): Path to the file being trackedaction (string, required): Action performed on the file (open, edit, close, etc.)metadata (object, optional): Additional metadata for the tracking event
Returns:
- Object with status, filename, action and timestamp
mcp_cursor10x_getRecentMessages
Retrieves recent messages from the short - term memory.
Parameters:
limit (number, optional): Maximum number of messages to retrieve, defaults to 10importance (string, optional): Filter by importance level
Returns:
- Object with status and array of messages
mcp_cursor10x_getActiveFiles
Retrieves active files from the short - term memory.
Parameters:
limit (number, optional): Maximum number of files to retrieve, defaults to 10
Returns:
- Object with status and array of active files
Long - Term Memory Tools
mcp_cursor10x_storeMilestone
Stores a project milestone in the long - term memory.
Parameters:
title (string, required): Title of the milestonedescription (string, required): Description of the milestoneimportance (string, optional): Importance level, defaults to "medium"metadata (object, optional): Additional metadata for the milestone
Returns:
- Object with status, title, and timestamp
mcp_cursor10x_storeDecision
Stores a project decision in the long - term memory.
Parameters:
title (string, required): Title of the decisioncontent (string, required): Content of the decisionreasoning (string, optional): Reasoning behind the decisionimportance (string, optional): Importance level, defaults to "medium"metadata (object, optional): Additional metadata for the decision
Returns:
- Object with status, title, and timestamp
mcp_cursor10x_storeRequirement
Stores a project requirement in the long - term memory.
Parameters:
title (string, required): Title of the requirementcontent (string, required): Content of the requirementimportance (string, optional): Importance level, defaults to "medium"metadata (object, optional): Additional metadata for the requirement
Returns:
- Object with status, title, and timestamp
Episodic Memory Tools
mcp_cursor10x_recordEpisode
Records an episode (action) in the episodic memory.
Parameters:
actor (string, required): Actor performing the action (user, assistant, system)action (string, required): Type of action performedcontent (string, required): Content or details of the actionimportance (string, optional): Importance level, defaults to "low"context (string, optional): Context for the episode
Returns:
- Object with status, actor, action, and timestamp
mcp_cursor10x_getRecentEpisodes
Retrieves recent episodes from the episodic memory.
Parameters:
limit (number, optional): Maximum number of episodes to retrieve, defaults to 10context (string, optional): Filter by context
Returns:
- Object with status and array of episodes
Vector - Based Memory Tools
mcp_cursor10x_manageVector
Unified tool for managing vector embeddings with operations for store, search, update, and delete.
Parameters:
operation (string, required): Operation to perform ("store", "search", "update", "delete")contentId (number, optional): ID of the content this vector represents (for store, update, delete)contentType (string, optional): Type of content ("message", "file", "snippet", etc.)vector (array, optional): Vector data as array of numbers (for store, update) or query vector (for search)vectorId (number, optional): ID of the vector to update or deletelimit (number, optional): Maximum number of results for search operation, defaults to 10threshold (number, optional): Similarity threshold for search operation, defaults to 0.7metadata (object, optional): Additional info about the vector
Returns:
- Object with status and operation results
๐ง Technical Details
System Architecture
The memory system is built on four core components:
- MCP Server: Implements the Model Context Protocol to register tools and process requests
- Memory Database: Uses Turso database for persistent storage across sessions
- Memory Subsystems: Organizes memory into specialized systems with distinct purposes
- Vector Embeddings: Transforms text and code into numerical representations for semantic search
Memory Types
The system implements four complementary memory types:
-
Short - Term Memory (STM)
- Stores recent messages and active files
- Provides immediate context for current interactions
- Automatically prioritizes by recency and importance
-
Long - Term Memory (LTM)
- Stores permanent project information like milestones and decisions
- Maintains architectural and design context
- Preserves high - importance information indefinitely
-
Episodic Memory
- Records chronological sequences of events
- Maintains causal relationships between actions
- Provides temporal context for project history
-
Semantic Memory
- Stores vector embeddings of messages, files, and code snippets
- Enables retrieval of content based on semantic similarity
- Automatically indexes code structures for contextual retrieval
- Tracks relationships between code components
- Provides similarity - based search across the codebase
Database Schema
The memory system automatically creates and maintains the following database tables:
-
messages: Stores user and assistant messages
id: Unique identifiertimestamp: Creation timestamprole: Message role (user/assistant)content: Message contentimportance: Importance levelarchived: Whether the message is archived
-
active_files: Tracks file activity
id: Unique identifierfilename: Path to the fileaction: Last action performedlast_accessed: Timestamp of last access
-
milestones: Records project milestones
id: Unique identifiertitle: Milestone titledescription: Detailed descriptiontimestamp: Creation timestampimportance: Importance level
-
decisions: Stores project decisions
id: Unique identifiertitle: Decision titlecontent: Decision contentreasoning: Decision reasoningtimestamp: Creation timestampimportance: Importance level
-
requirements: Maintains project requirements
id: Unique identifiertitle: Requirement titlecontent: Requirement contenttimestamp: Creation timestampimportance: Importance level
-
episodes: Chronicles actions and events
id: Unique identifiertimestamp: Creation timestampactor: Actor performing the actionaction: Type of actioncontent: Action detailsimportance: Importance levelcontext: Action context
-
vectors: Stores vector embeddings for semantic search
id: Unique identifiercontent_id: ID of the referenced contentcontent_type: Type of content (message, file, snippet)vector: Binary representation of the embedding vectormetadata: Additional metadata for the vector
-
code_files: Tracks indexed code files
id: Unique identifierfile_path: Path to the filelanguage: Programming languagelast_indexed: Timestamp of last indexingmetadata: Additional file metadata
-
code_snippets: Stores extracted code structures
id: Unique identifierfile_id: Reference to the parent filestart_line: Starting line numberend_line: Ending line numbersymbol_type: Type of code structure (function, class, variable)content: The code snippet content
Example Workflows
Optimized Conversation Start
const result = await mcp_cursor10x_initConversation({
content: "I need help implementing authentication in my React app",
importance: "high",
});
console.log("Memory System Status:", result.display.banner);
const context = result.internal.context;
Starting a New Session (Alternative Method)
mcp_cursor10x_generateBanner({});
mcp_cursor10x_getComprehensiveContext({});
mcp_cursor10x_storeUserMessage({
content: "I need help with authentication",
importance: "high",
});
Tracking User Activity
await mcp_cursor10x_trackActiveFile({
filename: "src/auth/jwt.js",
action: "edit",
});
Troubleshooting
Common Issues
-
Database Connection Problems
- Verify your Turso database URL and authentication token are correct
- Check network connectivity to the Turso service
- Verify firewall settings allow the connection
-
Missing Data
- Check that data was stored with appropriate importance level
- Verify the retrieval query parameters (limit, filters)
- Check the database health with
mcp_cursor10x_checkHealth()
-
Performance Issues
- Monitor memory statistics with
mcp_cursor10x_getMemoryStats()
- Consider archiving old data if database grows too large
- Optimize retrieval by using more specific filters
Diagnostic Steps
-
Check system health:
const health = await mcp_cursor10x_checkHealth({});
console.log("System Health:", health);
-
Verify memory statistics:
const stats = await mcp_cursor10x_getMemoryStats({});
console.log("Memory Stats:", stats);
-
Generate a status banner:
const banner = await mcp_cursor10x_generateBanner({});
console.log("Memory Banner:", banner);
Importance Levels
When storing items in memory, use appropriate importance levels:
- low: General information, routine operations, everyday conversations
- medium: Useful context, standard work items, regular features
- high: Critical decisions, major features, important architecture elements
- critical: Core architecture, security concerns, data integrity issues
๐ License
MIT
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