Contextra
byMorasami
0Provides persistent memory capabilities for AI agents, enabling them to learn and recall information across conversations.
About
Contextra is an MCP (Model Context Protocol) Memory Server designed to equip AI agents with persistent memory. It allows agents to learn and recall past interactions and information, functioning as a structured storage and retrieval system. The system employs a two-stage retrieval workflow, optimizing token usage by first providing memory summaries for agent preview, followed by selective retrieval of full content, ensuring efficient access to comprehensive information.
Key Features
- Employs an agent-driven architecture, keeping cognitive processing with the AI agent.
- Includes MCP-native guidance through built-in prompts for effective agent usage.
- Offers five canonical MCP tools for memory operations (write, search, retrieve, list, inspect).
- Provides local-first storage for full data control and privacy.
- 0 GitHub stars
- Features a lightweight-first design utilizing SQLite and ChromaDB, with no external dependencies.
Use Cases
- Enhancing GitHub Copilot's memory and contextual understanding within VS Code.
- Optimizing token usage for AI agents by implementing a two-stage memory retrieval process.
- Enabling AI agents to store, search, and retrieve relevant information from past interactions.
Sponsored