A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
244 ★ · scarletkc/vexor · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 244 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository scarletkc/vexor;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
--- **Vexor** is a semantic search engine that builds reusable indexes over files and code. It supports configurable embedding and reranking providers, and exposes the same core through a Python API, a CLI tool, and an MCP server. Vexor Demo Video Featured In Vexor has been recognized and featured by the community: - **Ruan Yifeng's Weekly (Issue #379)** - A leading tech newsletter in the Chinese developer community. - **Awesome Claude Skills** - Curated list of best-in-class skills for AI agents. - **Awesome MCP Servers** - Curated list of Model Context Protocol servers. - **Awesome CLI Apps** - Curated list of command-line apps. Why Vexor? When you remember what a file *does* but forget its name or location, Vexor finds it instantly—no grep patterns or directory traversal needed. Designed for both humans and AI coding assistants, enabling semantic file discovery in autonomous agent workflows. Install Download standalone binary from releases (no Python required), or: Quick Start 0. Guided Setup (Recommended) The wizard also runs automatically before the first interactive operational command when no config exists. Configuration-management (vexor config), MCP, help, and version commands run directly. 1. Search Vexor auto-indexes on first search. Example output: 2. Explicit Index (Optional) Useful for CI warmup or when auto_index is disabled. Python API Vexor can also be imported and used directly from Python: Configuration follows the same global and project-level resolution as the CLI. For runtime overrides, cache controls, and per-call options, see docs/api/python.md. AI Agent Skill This repo includes a skill for AI agents to use Vexor effectively: Skill source: plugins/vexor/skills/vexor-cli MCP Server > [!NOTE] > The Agent Skill and the MCP server provide the same core capability — pick **one** per agent. > The skill teaches shell-capable agents (Claude Code, Codex) to drive the full CLI and assumes vexor is installed on PATH; the MCP server exposes search as native tools, works in any MCP client (Cursor, Windsurf, Zed, ...), and can bootstrap without prior setup via uvx and environment variables. Vexor ships a built-in MCP stdio server, so any MCP-capable agent can use semantic file search as a native tool: Or configure manually in any MCP client, optionally supplying the API key and any config overrides via env (no vexor init needed): The server exposes two tools: vexor_search (semantic file search, returning the matching source text so an agent rarely needs a follow-up file read) and vexor_index (explicit index warm-up). No extra dependencies are required. Vexor is listed on the official MCP registry as io.github.scarletkc/vexor. See docs/mcp.md for tool schemas, environment variables, and client setup details. Configuration Global config lives in ~/.vexor/config.json; the nearest /.vexor/config.json can override a restricted set of behavior fields