Seahorse is an innovative solution for persistent, bi-temporal memory tailored for Large Language Model (LLM) agents. Unlike conventional memory systems that start anew with each session, Seahorse maintains continuity, allowing agents to remember key context and decisions across interactions. Here are the core features that set Seahorse apart:

Key Features

• Persistent Memory: Seahorse allows agents to retain knowledge across sessions, eliminating the issue of starting from scratch each time. This memory structure is bi-temporal, which supports tracking when data was created and when it remains valid.
• Openness and Portability: It utilizes an open, portable memory format designed to ensure easy migration between different systems without vendor lock-in. Users can edit and manage their memories in a human-readable format using Markdown, promoting transparency and usability.
• User-Centric Design: The memory interface is built to accommodate both agents and human interaction, allowing users to directly modify and audit memory records. This creates a system where corrections can be applied in real time, enhancing information accuracy.
• Cost-Effective: Avoid the high costs associated with traditional memory tools that require frequent interaction with LLMs by employing a memory system that significantly reduces the number of necessary writes.
• Avoid Vendor Lock-in: Seahorse is designed to be ecosystem-agnostic, meaning that users are not tied to any specific provider's runtime or environment.

Use Cases

1. For Developers Building Agents: Whether using mainstream agents like Claude Code or building custom solutions, developers can easily implement Seahorse to improve memory utilization.
2. For Obsidian Users: Power users can enhance their note-taking experience by integrating Seahorse into their workflows, turning static archives into dynamic knowledge bases.
3. For Teams: Teams can benefit from a memory format that ensures data portability, allowing them to switch vendors or tools without losing historical context.

Example of Usage

To effectively utilize Seahorse, follow these steps with the command-line tool:

# Initialize a new memory vault
seahorse init myvault

# Store a memory
seahorse remember "Sergio lives in Madrid"

# Recall stored information
seahorse recall "where does Sergio live?"

How it Works

Seahorse operates through an MCP (Memory Control Protocol) server which integrates seamlessly with agents, promoting efficient interactions for memory writing and retrieval. It leverages SQLite for storage while employing Markdown files for human-readable data management, ensuring that both agents and users can effectively manage and access memory resources.

Use Case: Memory for Claude Code

Improve the capabilities of Claude Code by integrating persistent memory:

• Capture sessions with seahorse setup and start the observation to record interactions.
• Recall past decisions using commands like seahorse recall to access previously saved context.
• Import existing memory formats into your Seahorse vault without losing data.

Conclusion

Seahorse presents a robust solution for managing persistent memory within LLM agent systems. By offering portability, transparency, and user-centric features, it empowers developers and teams to create more adaptive and knowledgeable agents.