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Vexor

by scarletkcversion 0.31.0i★ –iRuns on your computer
Registry nameio.github.scarletkc/vexor

Install

Overview

Description from the maker (original English)

A semantic search engine for files and code.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Docs, sheets & office work
  • You need to fill in: VEXOR_API_KEY, VEXOR_REMOTE_RERANK_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: VEXOR_API_KEY, VEXOR_REMOTE_RERANK_API_KEY, VEXOR_CONFIG_JSON

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "vexor": {
      "command": "uvx",
      "args": [
        "vexor",
        "mcp"
      ],
      "env": {
        "VEXOR_API_KEY": "your-value",
        "VEXOR_REMOTE_RERANK_API_KEY": "your-value",
        "VEXOR_CONFIG_JSON": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add vexor --env VEXOR_API_KEY=your-value --env VEXOR_REMOTE_RERANK_API_KEY=your-value --env VEXOR_CONFIG_JSON=your-value -- uvx vexor mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "vexor": {
      "command": "uvx",
      "args": [
        "vexor",
        "mcp"
      ],
      "env": {
        "VEXOR_API_KEY": "your-value",
        "VEXOR_REMOTE_RERANK_API_KEY": "your-value",
        "VEXOR_CONFIG_JSON": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "vexor": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "vexor",
        "mcp"
      ],
      "env": {
        "VEXOR_API_KEY": "your-value",
        "VEXOR_REMOTE_RERANK_API_KEY": "your-value",
        "VEXOR_CONFIG_JSON": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • VEXOR_API_KEY secret env
    Embedding provider API key (optional; overrides a stored key; providers can also be configured via `vexor init`)
  • VEXOR_REMOTE_RERANK_API_KEY secret env
    Remote reranker API key (optional; overrides a stored key; only needed when rerank is set to remote)
  • VEXOR_CONFIG_JSON env
    Non-secret Vexor config as a JSON object, e.g. {"provider": "gemini", "rerank": "bm25"} (optional; merged over ~/.vexor/config.json; credential fields are rejected, use the dedicated variables)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account scarletkc, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Docs, sheets & office worki

  • More stars than 0% of the other 3538 servers in this category
  • Published to the registry more recently than 76% of the other 3538 servers in this category
  • Basic checks equal to or better than 100% of the other 3538 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Vexor safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: VEXOR_API_KEY, VEXOR_REMOTE_RERANK_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.31.0) reached the registry 10 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Agent-Native Google Calendar - manage events, sync, and public booking

Runs in the cloud★ 7,620MITUpdated 2 months ago
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Excel MCP Server

by haris-musa

Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.

Runs on your computer★ 4,276MITUpdated 7 days ago
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Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

Runs on your computer★ 847MITUpdated 4 days ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Vexor


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)](https://github.com/ruanyf/weekly/blob/master/docs/issue-379.md#ai-%E7%9B%B8%E5%85%B3) - A leading tech newsletter in the Chinese developer community.
  • [Awesome Claude Skills](https://github.com/VoltAgent/awesome-claude-skills?tab=readme-ov-file#development-and-testing) - Curated list of best-in-class skills for AI agents.
  • [Awesome MCP Servers](https://github.com/punkpeye/awesome-mcp-servers#-developer-tools) - Curated list of Model Context Protocol servers.
  • [Awesome CLI Apps](https://github.com/agarrharr/awesome-cli-apps#search) - 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:

pip install vexor  # also works with pipx, uv

Quick Start

0. Guided Setup (Recommended)
vexor init

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 "api client config"  # defaults to search current directory

or explicit path:

vexor search "api client config" --path ~/projects/demo --top 5

in-memory search only:

vexor search "api client config" --no-cache

Vexor auto-indexes on first search. Example output:

Vexor semantic file search results

──────────────────────────────────

Similarity File path Lines Preview

1 0.923 ./src/config_loader.py - config loader entrypoint 2 0.871 ./src/utils/config_parse.py - parse config helpers 3 0.809 ./tests/test_config_loader.py - tests for config loader

2. Explicit Index (Optional)
vexor index  # indexes current directory

or explicit path:

vexor index --path ~/projects/demo --mode code

Useful for CI warmup or when `auto_index` is disabled.

Python API

Vexor can also be imported and used directly from Python:

from vexor import index, search

index(path=".", mode="head") response = search("config loader", path=".", mode="name")

for hit in response.results: print(hit.path, hit.score)

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:

vexor install --skills claude  # Claude Code

vexor install --skills codex # Codex

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:

claude mcp add vexor -- vexor mcp   # Claude Code

codex mcp add vexor -- vexor mcp # Codex

Or configure manually in any MCP client, optionally supplying the API key and any config overrides via env (no vexor init needed):

{

"mcpServers": { "vexor": { "command": "vexor", "args": ["mcp"], "env": { "VEXOR_API_KEY": "sk-...", "VEXOR_CONFIG_JSON": "{\"provider\": \"gemini\", \"rerank\": \"bm25\"}" } } } }

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

vexor init                             # guided setup (recommended)

vexor config --set-api-key "YOUR_KEY" # or env: VEXOR_API_KEY / OPENAI_API_KEY / ... vexor config --set-provider openai # default; also gemini/voyageai/custom/local vexor config --rerank hybrid # optional: fuse exact keyword + semantic ranking vexor config --show # view effective settings and origins

Global config lives in ~/.vexor/config.json; the nearest /.vexor/config.json can override a restricted set of behavior fields for that project. Non-secret fields can also be injected via VEXOR_CONFIG_JSON (useful for MCP clients and CI), and fully offline use is supported through local embedding models.

See docs/configuration.md for the complete reference: project config fields and precedence, all config commands, API keys and environment variables, rerank strategies (hybrid / BM25 / FlashRank / remote), remote vs local providers, embedding dimensions, and offline local model setup.

CLI Reference

Everyday usage fits in vexor "query", vexor search, and vexor index (see Quick Start). The full command table, common flags, index modes (--mode auto/name/head/brief/full/code/outline), .vexorignore files, project-local indexes (vexor index --local), cache behavior, and porcelain output format are documented in docs/cli.md.

Documentation

  • Configuration — providers, API keys, rerank, embedding dimensions, local models
  • CLI reference — commands, flags, index modes, cache behavior
  • MCP server — client setup, environment variables, tool schemas
  • Python API — programmatic usage
  • Collections API — database-backed text records and filtered search

Contributing

Contributions, issues, and PRs welcome! Commit messages and PR titles follow Conventional Commits (e.g. feat(mcp): add stdio server). Star if you find it helpful.

Star History

License

MIT

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