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Gives AI coding agents persistent memory and semantic file discovery across sessions.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "RLM Memory MCP Server" yet — see the docs or source repo.
Please read the saved project memory, summarize which modules I changed last time and what tasks remain, then continue the user login refactor.
A summary of prior work, relevant context, and actionable refactor steps or code changes.
Find the files most relevant to permission checks, middleware interception, and role-based access control, and explain each file's role.
A list of relevant files with semantic-match explanations and useful investigation clues.
Store in long-term memory the reasons, impact scope, and follow-up notes for switching the cache layer from Redis client A to client B.
The key decision is saved as reusable memory for future sessions and continued development.
Give AI coding agents persistent semantic memory with embedding-based retrieval.
Analyze massive codebases beyond context limits with recursive LLM search.
Give AI coding assistants persistent memory and full-text knowledge retrieval.
Provides durable local memory for LLM coding workflows.
Give AI coding agents long-term memory, search, and organization across sessions.
Give AI agents persistent memory, shared reasoning, and auditable collaboration.