by 1ch1n · MCP Server · ★ 65
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/1ch1n/mychatarchive.gitTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 65 |
| Forks | 17 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 67/100 |
| Open Issues | 6 |
| Last Updated | 2026-08-05 |
| Created | 2025-11-11 |
| Platforms | claude-code, cli, mcp, python |
| Est. Tokens | ~17k |
MyChatArchive Your AI conversation history, locally searchable by meaning. Quick Start · <a href="#w
These tools work well together with mychatarchive for enhanced workflows:
Looking for a mychatarchive alternative? If you're comparing mychatarchive 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.
Persistent memory for AI coding agents
MCP server that lets Claude Code and other AI agents read and search large PDFs, one file or a whole folder: a
🦀 Prevents outdated Rust code suggestions from AI assistants. This MCP server fetches current crate docs, use
On-device memory layer for AI agents. Claude Code, OpenClaw and Hermes. Hooks + MCP server + hybrid RAG search
📜 An MCP server for conversation history search and retrieval in Claude Code
Node.js/TypeScript MCP server for Atlassian Bitbucket. Enables AI systems (LLMs) to interact with workspaces,
Explore other popular mcp server tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: