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Read and write persistent Markdown memory for MCP-compatible coding agents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "everos-mcp" yet — see the docs or source repo.
Please write the project's key constraints, naming rules, and to-dos into persistent memory for later development.
Writes the information into EverOS persistent Markdown memory.
Please read the memory related to this repository and summarize the most important background context.
Retrieves and summarizes relevant context from persistent memory.
Update the memory with the new code review conventions and API change notes, replacing the old version.
Updates team conventions and change notes in Markdown memory.
Developers who work across multiple coding sessions need the agent to remember constraints, decisions, and tasks. This tool persists that context for later use.
When you want memory stored as Markdown for easy human inspection and updates, this tool can read and write that persisted content.
For MCP-supported coding agents, it provides access to external persistent memory through the EverOS REST API.
It lets MCP-compatible coding agents read and write persistent Markdown memory through the EverOS REST API. It is useful for storing and retrieving project context, conventions, and notes.
You need an MCP-compatible coding agent and access to the EverOS REST API. For the remaining installation or configuration details, see the source repository.
It is designed for MCP agents, focusing on programmatic read/write access to persistent memory rather than only human viewing. The memory is stored in Markdown for readability and editing.
Persistent memory for coding agents across sessions
Give AI coding agents persistent semantic memory with embedding-based retrieval.
Give AI coding assistants persistent memory for preferences, build steps, and architecture decisions.
Query Everlog diary exports for reflection, evidence retrieval, and self-model maintenance.
Manage persistent agent memories across global or repository-specific scopes.
Give AI coding assistants long-term memory across sessions for persistent context.