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Fast and Accurate Code Search for Agents. Uses ~98% fewer tokens than grep+read

MCP Servers5.1k estrellas219 forksPythonMITActualizado today
Nota editorial

Semble is a Python MCP server that provides semantic code search for AI coding agents, indexing a full repository in roughly 250 milliseconds and returning query results in about 1.5 milliseconds, entirely on CPU with no API keys or GPU required. It integrates with Claude Code, Cursor, Codex, OpenCode, and any other MCP-compatible agent through three deployment modes: an MCP server tool, CLI instructions injected into AGENTS.md or CLAUDE.md, and a dedicated sub-agent named semble-search. An interactive installer detects which coding agents are present and configures the chosen integrations automatically. Rather than passing full file contents to the agent, Semble returns only the relevant code chunks, which the project benchmarks at roughly 98 percent fewer tokens than a grep-plus-read approach while achieving an NDCG@10 of 0.854, comparable to code-specialized transformer models. The CLI supports natural-language queries against local paths or remote git URLs, a find-related command for locating code similar to a known file and line, and a savings command that displays cumulative token savings across all searches.

ClaudeWave Trust Score
100/100
Verified
Passed
  • Open-source license (MIT)
  • Actively maintained (<30d)
  • Clear description
  • Topics declared
  • Documented (README)
Last scanned: 6/11/2026
Install in Claude Code / Claude Desktop
Method: UVX (Python) · semble
Claude Code CLI
claude mcp add semble -- uvx semble
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "semble": {
      "command": "uvx",
      "args": ["semble"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Package name inferred from the repository name. Verify it exists on PyPI, or clone https://github.com/MinishLab/semble and follow its README.
Casos de uso

Resumen de MCP Servers

README no disponible. Visita el repo en GitHub para la documentación completa.
agentscode-searchembeddingsmcpmcp-servermodel-context-protocolretrieval

Lo que la gente pregunta sobre semble

¿Qué es MinishLab/semble?

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MinishLab/semble es mcp servers para el ecosistema de Claude AI. Fast and Accurate Code Search for Agents. Uses ~98% fewer tokens than grep+read Tiene 5.1k estrellas en GitHub y se actualizó por última vez today.

¿Cómo se instala semble?

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Puedes instalar semble clonando el repositorio (https://github.com/MinishLab/semble) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar MinishLab/semble?

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Nuestro agente de seguridad ha analizado MinishLab/semble y le ha asignado un Trust Score de 100/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene MinishLab/semble?

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MinishLab/semble es mantenido por MinishLab. La última actividad registrada en GitHub es de today, con 6 issues abiertos.

¿Hay alternativas a semble?

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Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.

Despliega semble en tu cloud

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