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Search files and code semantically to find relevant content faster.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Vexor" MCP server from askskill: Run: claude mcp add 'io-github-scarletkc-vexor' -- uvx vexor
Semantically search the current project for code related to "handling user login failures and retry logic," and return filenames and snippets ranked by relevance.
A ranked list of relevant code files, matching snippets, and brief relevance results.
Search for files semantically closest to "API authentication flow documentation," including docs, comments, or design notes.
Relevant documents or text files that help quickly locate explanatory material.
Find all files and code snippets in the project related to the "export reports" feature.
A list of files and corresponding snippets related to the feature for further analysis.
Developers working in an unfamiliar project can use it to find code related to a feature or logic by meaning instead of exact keywords. This helps them locate implementations and context faster.
Researchers or analysts can search a collection of files for content most related to a topic. It fits situations where they need to quickly surface useful clues from files and code.
Vexor is a semantic search engine for files and code. It helps find relevant content by meaning, not just exact keywords.
Based on the given description, it can search files and code. For specific file types or support details, see the source repository.
The provided material does not include installation steps, runtime requirements, or key requirements. See the source repository for details.
Search codebases semantically with natural language to find relevant files and logic.
Search indexed codebases semantically with natural language across MCP clients.
Search the live web and codebase in real time for company research and information retrieval.
Search project docs semantically to find relevant files before coding changes.
Search code quickly and accurately while using far fewer tokens.
Use Exa neural search for web, code, company, and people research.