mcpField
C
ContextBase (MCP Server)

ContextBase (MCP Server)

Local
contextbase.onrender.comMemory & Knowledge1Updated 80w ago

About ContextBase (MCP Server)

ContextBase is an MCP server for AI agents, assistants, and apps to store, retrieve, and manage per-user context through an API. It combines persistent memory endpoints with authentication, logging, and database-backed storage.

Key features

  1. 01Store and retrieve user memories
  2. 02Create, update, and delete memories
  3. 03JWT authentication
  4. 04User action logs
  5. 05PostgreSQL storage and Redis caching

Use cases

  1. 01Give an AI app access to per-user context
  2. 02Manage stored memories through API endpoints
  3. 03Review recorded user actions

MCP support

Provides an MCP server for AI agents, assistants, and apps managing user context. The README describes memory and account functions through API endpoints.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

ContextBase (MCP Server)

ContextBase – A Model Context Protocol (MCP) server for AI agents, assistants, and apps which store, retrieve, and manage per-user context using a simple API.

Features

  • Authentication System: Secure user authentication using JWT and bcrypt
  • Memory Management: API endpoints for storing and retrieving memory data
  • Logging System: Comprehensive logging of user actions
  • Modern Tech Stack: Built with TypeScript, Fastify, Prisma ORM
  • Database Integration: PostgreSQL for persistent storage
  • Caching: Redis for high-performance caching

Prerequisites

  • Node.js (v14 or higher)
  • PostgreSQL
  • Redis
  • Docker and Docker Compose (optional, for containerized deployment)

Installation

  1. Clone the repository

    git clone https://github.com/imfeniljikadara/contextbase.git
    cd mcp
    
  2. Install dependencies

    cd mcp-server
    npm install
    
  3. Set up environment variables Create a .env file in the mcp-server directory with the following variables:

    DATABASE_URL=postgresql://username:password@localhost:5432/mcp
    REDIS_HOST=localhost
    REDIS_PORT=6379
    JWT_SECRET=your_jwt_secret
    PORT=3000
    
  4. Run database migrations

    npx prisma migrate dev
    
  5. Start the server

    npm start
    

    Or using Docker:

    docker-compose up
    

API Endpoints

  • Authentication

    • POST /api/auth/register - Register a new user
    • POST /api/auth/login - Login and get JWT token
  • Memory

    • GET /api/memory - Get all memories
    • POST /api/memory - Create a new memory
    • GET /api/memory/:id - Get a specific memory
    • PUT /api/memory/:id - Update a memory
    • DELETE /api/memory/:id - Delete a memory
  • Logs

    • GET /api/logs - Get user action logs

Development

  • Run in development mode:

    npm run dev
    
  • Run tests:

    npm test
    

Project Structure

mcp-server/
├── prisma/              # Database schema and migrations
├── src/
│   ├── api/             # API routes and controllers
│   ├── config/          # Configuration files
│   ├── db/              # Database connections (PostgreSQL, Redis)
│   ├── middleware/      # Custom middleware
│   ├── models/          # Data models
│   ├── services/        # Business logic
│   ├── utils/           # Utility functions
│   └── index.ts         # Application entry point
├── scripts/             # Helper scripts
├── .env                 # Environment variables
└── package.json         # Dependencies and scripts

License

MIT

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.