Memory Server
Provides persistent memory management using SQLite database, allowing storage, retrieval, and deletion of conversational context with metadata.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Memory Serversave that the user prefers cold weather"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Memory Server - MCP Server for Persistent Memory Management
A TypeScript-based Model Context Protocol (MCP) server that provides persistent memory management using SQLite database. This server exposes both MCP tools and RESTful API endpoints for storing and retrieving conversational context with metadata.
Features
SQLite Database Integration: Persistent storage with automatic schema creation and indexing
MCP Protocol Compliance: Full support for MCP tool registration and execution
RESTful API: HTTP endpoints for programmatic access
TypeScript: Full type safety and modern async/await patterns
Logging: Comprehensive logging with configurable levels
Error Handling: Robust error handling and input validation
Database Connection Pooling: Optimized database performance
Modular Architecture: Clean separation of concerns
Related MCP server: identity-storage-mcp
Database Schema
The server automatically creates a SQLite database with the following schema:
CREATE TABLE memory (
id INTEGER PRIMARY KEY AUTOINCREMENT,
content TEXT NOT NULL,
timestamp TEXT NOT NULL,
session_id TEXT NOT NULL,
content_hash TEXT NOT NULL UNIQUE,
metadata TEXT,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP
);
-- Indexes for performance optimization
CREATE INDEX idx_session_id ON memory(session_id);
CREATE INDEX idx_timestamp ON memory(timestamp);
CREATE INDEX idx_content_hash ON memory(content_hash);
CREATE INDEX idx_created_at ON memory(created_at);Installation
Clone or create the project directory
Install dependencies:
npm installBuild the TypeScript code:
npm run buildUsage
MCP Mode (Stdio Transport)
To run as an MCP server using stdio transport:
npm start -- --mcp
# or
MCP_MODE=true npm startHTTP Server Mode
To run as a standalone HTTP server:
npm startThe server will start on http://localhost:3000 by default.
Environment Variables
PORT: HTTP server port (default: 3000)HOST: HTTP server host (default: localhost)DB_PATH: SQLite database file path (default: ./data/memory.db)DB_MAX_CONNECTIONS: Maximum database connections (default: 10)LOG_LEVEL: Logging level (debug, info, warn, error) (default: info)CORS_ORIGIN: Comma-separated list of allowed CORS originsMCP_MODE: Set to 'true' to run in MCP modeNODE_ENV: Environment (development, production)
MCP Tools
The server provides the following MCP tools:
save_memory
Saves content to memory with metadata.
Parameters:
content(string, required): The content to savesession_id(string, required): Session identifier for groupingmetadata(object, optional): Additional metadata
Example:
{
"content": "User prefers dark mode and uses TypeScript",
"session_id": "user-123-session-1",
"metadata": {
"category": "preferences",
"importance": "high"
}
}read_memory
Retrieves stored memories with optional filtering.
Parameters:
session_id(string, optional): Filter by session IDstart_date(string, optional): Filter from date (ISO format)end_date(string, optional): Filter until date (ISO format)limit(number, optional): Maximum records to return (1-1000)offset(number, optional): Records to skip for pagination
get_memory_count
Gets the total count of memory records.
Parameters:
session_id(string, optional): Count for specific session
delete_memory
Deletes a specific memory record.
Parameters:
id(number, required): ID of the memory record to delete
REST API Endpoints
POST /api/memory/save
Save a new memory record.
Request Body:
{
"content": "Content to save",
"session_id": "session-identifier",
"metadata": {
"key": "value"
}
}GET /api/memory/read
Read memory records with optional query parameters:
session_id: Filter by sessionstart_date: Filter from dateend_date: Filter until datelimit: Maximum recordsoffset: Pagination offset
GET /api/memory/count
Get memory count with optional session_id query parameter.
DELETE /api/memory/:id
Delete a specific memory record by ID.
GET /api/memory/health
Health check endpoint.
MCP Server Configuration
To use this server with an MCP client, add it to your MCP settings:
{
"mcpServers": {
"memory-server": {
"command": "node",
"args": ["path/to/memory-server/build/index.js", "--mcp"],
"env": {
"DB_PATH": "path/to/memory.db",
"LOG_LEVEL": "info"
}
}
}
}Development
Scripts
npm run build: Compile TypeScript to JavaScriptnpm run dev: Watch mode for developmentnpm start: Start the server
Project Structure
memory-server/
├── src/
│ ├── index.ts # Main server entry point
│ ├── database.ts # SQLite database operations
│ ├── api.ts # REST API routes
│ ├── mcp-tools.ts # MCP tool handlers
│ ├── logger.ts # Logging utility
│ └── types.ts # TypeScript interfaces
├── build/ # Compiled JavaScript (generated)
├── data/ # Database files (generated)
├── package.json
├── tsconfig.json
└── README.mdError Handling
The server includes comprehensive error handling:
Input validation for all endpoints and tools
Database connection error handling
Graceful shutdown on SIGTERM/SIGINT
Detailed error logging
Proper HTTP status codes
Performance Optimization
Database indexes on frequently queried columns
Connection pooling for database operations
Efficient query patterns
Content hashing to prevent duplicates
Configurable limits and pagination
Security Considerations
Input validation and sanitization
CORS configuration
Content hash verification
SQL injection prevention through parameterized queries
Error message sanitization in production
License
MIT License
This server cannot be deployed
Maintenance
Related MCP Connectors
Persistent memory for AI agents — log and recall conversation context over MCP.
Cross-tool persistent memory and context for AI assistants over MCP.
Shared, governed long-term memory for AI agents across tools and sessions via MCP and REST.
- HeirmosOAuthcom.heirmos
Persistent memory shared across Claude, ChatGPT, Grok and other MCP clients.
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