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Self-host shared memory, RAG search, and persistent context for AI agents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ai-hub" yet — see the docs or source repo.
Store the following project information in ai-hub shared memory: project name, target users, current milestone, and key constraints, then generate a project map for all future AI agents to reuse.
The shared memory is saved, with a reusable project context and project map for different AI tools.
Use ai-hub's RAG document search to find materials related to the API authentication flow and summarize them for the engineering team.
Relevant document search results are returned, along with a concise explanation for the team.
Configure role-based prompts in ai-hub for product manager, developer, and tester roles so different AI agents can answer the same project question from their own responsibilities.
Role-specific AI prompt configurations are created so agents can respond consistently within the same context.
Development or product teams can use it to centralize project memory, project maps, and role-based prompts so AI agents across devices and tools share the same context. This reduces repeated background explanations.
When teams need AI to answer questions from existing materials, they can use its RAG document search capability. It is suitable for finding information in project documents and providing more contextual answers.
Teams that want to run their own AI support infrastructure can use it to provide shared capabilities to multiple AI agents through MCP and REST. It fits scenarios that value unified access and persistent context.
It is a self-hosted server that provides shared memory, RAG document search, project maps, and role-based prompts for AI agents through MCP and REST, while maintaining persistent context across devices and tools.
Based on the description, it supports integration through MCP and REST, so it can act as a shared context layer for multiple AI agents. See the source repository for specific setup details.
It is known to be self-hosted, but the provided material does not include installation steps, runtime requirements, or key requirements. See the source repository for the exact prerequisites.
Persistent memory, code intelligence, and quality enforcement through one MCP endpoint.
Coordinate AI agent teams with shared memory, kanban workflows, and live oversight.
Shared project wiki for AI agents to manage pages, actions, and logs.
Centralize local AI chat history in SQLite and retrieve exact context via MCP.
Give AI agents self-organizing memory with hot cache and semantic search.
Build self-hosted visual AI workflows with agents, RAG, HITL, and observability.