by Thinklanceai · MCP Server · ★ 117
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
AgentKeeper Cognitive continuity infrastructure for long-lived AI agents. Your agent survives model switches, crashes, context-window limits, and restarts — with the same identity, memory, and priorities it had before. Why this exists Agents don't fail because they forget facts. They fail because they lose cognitive continuity — their state, priorities, and identity drift the moment the model changes, the context window fills, or the process restarts. AgentKeeper treats this as a systems problem, not a memory problem. Install Zero required dependencies. No external infrastructure. Storage defaults to local SQLite. bash pip install 'agentkeeper-ai[anthropic]' # Claude pip install 'agentkeeper-ai[openai]' # GPT + OpenAI embeddings pip install 'agentkeeper-ai[gemini]' # Gemini pip install '
| Stars | 117 |
| Forks | 17 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 55.304/100 |
| Last Updated | 2026-05-20 |
| Created | 2026-02-24 |
| Platforms | claude-code, gemini, mcp, python |
| Est. Tokens | ~27k |
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agentkeeper is Cognitive continuity infrastructure for long-lived AI agents — cross-model state reconstruction, semantic recall, cognitive compression.. It is categorized as a MCP Server with 117 GitHub stars.
agentkeeper is primarily written in Python. It covers topics such as agent-memory, agentic-ai, agents.
You can find installation instructions and usage details in the agentkeeper GitHub repository at github.com/Thinklanceai/agentkeeper. The project has 117 stars and 17 forks, indicating an active community.
agentkeeper is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agentkeeper on Agent Skills Hub include mira-OSS, agent-builder, mcp-server. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.