Potencia tu agente
El comando propio del publicador. No es un endpoint de PlugMCP.
Host a copy with our keys and logs.
uvx vexor==0.31.0Claude Code no tiene enlace de instalación para un comando local. Copia el comando de abajo y ejecútalo en una terminal.
VEXOR_API_KEY=<secret> VEXOR_REMOTE_RERANK_API_KEY=<secret> VEXOR_CONFIG_JSON=<value> claude mcp add scarletkc-vexor -- uvx vexor==0.31.0Ejecútalo en una terminal.
{ "mcpServers": { "scarletkc-vexor": { "command": "uvx", "args": [ "vexor==0.31.0" ], "env": { "VEXOR_API_KEY": "<secret>", "VEXOR_REMOTE_RERANK_API_KEY": "<secret>", "VEXOR_CONFIG_JSON": "<value>" } } }}claude_desktop_config.json
¿URL remota o un comando en tu máquina? En qué se diferencian las dos instalaciones
Ejecutar en PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
AbrirVexor 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 has been recognized and featured by the community:
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.
Download standalone binary from releases (no Python required), or:
pip install vexor # also works with pipx, uv
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.
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
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.
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.
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
[!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
vexoris 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 viauvxand 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.
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
<project>/.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.
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.
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.
A semantic search engine for files and code.
{ "mcpServers": { "scarletkc-vexor": { "command": "uvx", "args": [ "vexor==0.31.0" ], "env": { "VEXOR_API_KEY": "<secret>", "VEXOR_REMOTE_RERANK_API_KEY": "<secret>", "VEXOR_CONFIG_JSON": "<value>" } } }}Herramientas
Aún no hay lista de herramientas. Los servidores remotos la reciben tras la primera comprobación de estado.
Preguntas frecuentes
Copia en esta página la configuración stdio para Cursor, Claude Desktop, Claude Code o VS Code. Usa la instalación del publicador, no un proxy de PlugMCP.
El publicador indica estas variables de entorno: VEXOR_API_KEY, VEXOR_REMOTE_RERANK_API_KEY, VEXOR_CONFIG_JSON.
Vexor se ejecuta localmente por stdio.
Última comprobación: 2026-10-26. A semantic search engine for files and code.