Context Storage
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Provides persistent multimodal context storage for LLM agents, enabling seamless context sharing across multiple agents.
About
The Context Storage tool is a high-performance Model Context Protocol (MCP) server designed for LLM agents. It offers persistent storage for multimodal context, including text and images, facilitating seamless context sharing among agents collaborating on the same task. Built with FastMCP, it ensures compliance with the MCP standard and integrates smoothly with clients like Claude Code and LangGraph, offering robust features for organization, retrieval, and production readiness.
Key Features
- Multimodal Context Storage for text and images
- Thread-Based Scoping for shared context within tasks
- Tag-Based Organization for efficient context retrieval
- High Performance with SQLite, indexing, and async operations
- MCP Standard Compliance for integration with various clients
- 0 GitHub stars
Use Cases
- Storing and retrieving dynamic multimodal context for LLM agents
- Enabling collaborative context sharing among multiple AI agents on a single task
- Integrating a persistent memory solution into MCP-compatible AI frameworks like Claude Code or LangGraph
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