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Build a local-first second brain with semantic search over Markdown notes.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.evan-moon/memex" MCP server from askskill: Run: claude mcp add 'io-github-evan-moon-memex' -- npx -y @evan-moon/memex
Search my Markdown notes semantically for content related to "key pain points from user interviews" and summarize the most relevant results.
Returns semantically relevant notes with a brief summary.
Using my existing Markdown notes, find entries related to "local-first knowledge management" and list the key ideas.
Aggregates relevant notes and extracts the main themes.
Find content in my Markdown notes semantically related to "topics for my next article" and organize it into a candidate list.
Outputs relevant note snippets and a usable shortlist of topic candidates.
Researchers, students, or writers can use Markdown notes as a personal knowledge base and retrieve relevant content with semantic search. It is useful when exact keyword matches are not enough but the topic is similar.
Privacy-conscious or local-first users can index Markdown notes locally to build a second brain. It fits workflows that do not want to rely on cloud-based note search.
When notes are spread across many Markdown files, users can review material by topic rather than by file name. This makes it easier to gather previously recorded ideas and signals.
It is a local-first second brain tool that supports semantic search over Markdown notes. Its indexing is powered by a local machine learning model.
The provided information explicitly mentions Markdown notes. For support of other formats, see the source repository.
The description says it is local-first and indexed by a local machine learning model. For any extra service or key requirements, see the source repository.
Search local Markdown notes and manage tags, todos, and wiki links.
Let AI manage local Markdown notes as persistent memory across sessions.
Connect a personal Markdown knowledge base for secure note search, reading, and writing.
Build a local second brain with semantic memory recall and adaptive ranking.
Turn local notes into a private searchable knowledge base for AI assistants.
Provide persistent local semantic memory for MCP tools to store and search notes.