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Give AI coding agents persistent local knowledge, search, and structured context.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Kilonova MCP" MCP server from askskill: Run: claude mcp add 'io-github-milnaos-kilonova-mcp' -- npx -y kilonova-mcp
When a project evolves over time, developers can save key decisions, module relationships, and past issues as local knowledge for AI coding agents. This reduces the need to repeatedly explain project context.
When a team investigates recurring code or system issues, it can search existing records to quickly find relevant background and prior fixes. This is useful for debugging workflows that depend on historical context.
For projects with multiple modules or dependencies, structured records and DOT context can organize system knowledge so AI agents better understand component relationships. This fits complex codebases where context handoff matters.
It is an MCP tool for AI coding agents that provides persistent local knowledge, including structured records, search, and DOT context. Its focus is helping agents retain and retrieve development-related context.
Based on the description, it can handle structured records, searchable local knowledge, and DOT-based context information. For the exact data model and fields, see the source repository.
The provided material does not include installation steps, runtime requirements, or key setup details. Please see the source repository for exact setup and prerequisites.
Give AI coding agents persistent local memory across sessions.
Give AI coding agents persistent memory and codebase context retrieval.
Provide local-first memory and retrieval for coding agents using SQLite embeddings.
Give AI coding agents searchable local project memory with safe structured updates.
Give AI coding agents persistent memory across sessions for people, decisions, and context.
Give AI coding agents persistent memory across sessions for decisions and debugging context.