About Vecstor
🚀 First AI-Native Context Storage with Dual Protocol Support
The only production-ready platform that natively supports both REST APIs and Model Context Protocol (MCP) for seamless AI integration.
Vecstor is the AI-native context storage platform built specifically for the modern AI development workflow. From startups building their first AI chatbot to enterprises scaling production applications, we provide the dual-protocol infrastructure (REST + MCP) that developers actually need to build, scale, and maintain intelligent applications.
Why We Built Vecstor
Every AI developer faces the same challenge: building reliable context storage that works with both traditional web applications and emerging AI tools like Claude Desktop. Most solutions force you to choose between REST APIs or proprietary protocols.
We're different. Vecstor is the first platform built from the ground up to support both REST and Model Context Protocol (MCP) natively. This means you can use the same backend for your web app, your AI research tools, and direct Claude Desktop integration without any compromise.
Key Features
- Persistent Semantic Memory: Efficiently store and retrieve long-term context using state-of-the-art embedding models and vector databases (SQLite, ChromaDB, Qdrant, Pinecone).
- Advanced Search Capabilities: Semantic, hybrid, and temporal search with query expansion, auto-correction, and real-time analytics.
- SaaS Integrations: Direct connections to Google Drive, OneDrive for Business, Microsoft Teams, and Slack for automatic content synchronization.
- Vector Database Wrapper: A simplified, MCP-compatible interface abstracting interactions with various popular vector databases.
- Context Pre-processing Pipeline: An API-driven pipeline for cleaning, chunking, summarizing, and generating optimized embeddings from various document formats.
- Enterprise Security: Role-based access control (RBAC), API key management, and support for custom Pinecone databases.
- Performance & Scaling: Redis caching, async processing with Celery, and horizontal scaling support.
- Flexible Deployment: Available as a cloud-hosted service or a self-hosted solution (via Docker) for maximum control.
- Developer-Friendly API: Secure, well-documented RESTful API with OpenAPI specification for easy integration.
Whether you're building sophisticated AI agents, enhancing chatbot capabilities, or developing advanced RAG (Retrieval-Augmented Generation) systems, Vecstor provides the foundational infrastructure for managing semantic context effectively.