by savantskie · MCP Server · ★ 226
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
A persistent local memory for AI, LLMs, or Copilot in VS Code.
| Stars | 226 |
| Forks | 29 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 39.25/100 |
| Last Updated | 2026-04-23 |
| Created | 2025-08-02 |
| Platforms | mcp, python |
| Est. Tokens | ~67k |
These tools work well together with persistent-ai-memory for enhanced workflows:
Looking for a persistent-ai-memory alternative? If you're comparing persistent-ai-memory with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Memory that learns what works.
Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.
Persistent project knowledge graph for coding agents. MCP server with semantic search, in-process embeddings,
The Mind Palace for AI Agents - HIPAA-hardened Cognitive Architecture with on-device LLM (prism-coder:7b), Heb
The Mind Palace for AI Agents - HIPAA-hardened Cognitive Architecture with on-device LLM (prism-coder:7b), Heb
Persistent memory for AI coding agents. Cross-session context, global knowledge, and autonomous task execution
Explore other popular mcp server tools:
persistent-ai-memory is A persistent local memory for AI, LLMs, or Copilot in VS Code.. It is categorized as a MCP Server with 226 GitHub stars.
persistent-ai-memory is primarily written in Python. It covers topics such as ai-assistant, embeddings, github-copilot.
You can find installation instructions and usage details in the persistent-ai-memory GitHub repository at github.com/savantskie/persistent-ai-memory. The project has 226 stars and 29 forks, indicating an active community.
persistent-ai-memory is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to persistent-ai-memory on Agent Skills Hub include roampal, Ori-Mnemos, MegaMemory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.