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

MCP Servers5.1k stars219 forksPythonMITUpdated today
Editor's note

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.
Use cases

MCP Servers overview

README preview not available. Visit the repo on GitHub for full documentation.
agentscode-searchembeddingsmcpmcp-servermodel-context-protocolretrieval

What people ask about semble

What is MinishLab/semble?

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MinishLab/semble is mcp servers for the Claude AI ecosystem. Fast and Accurate Code Search for Agents. Uses ~98% fewer tokens than grep+read It has 5.1k GitHub stars and was last updated today.

How do I install semble?

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You can install semble by cloning the repository (https://github.com/MinishLab/semble) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is MinishLab/semble safe to use?

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Our security agent has analyzed MinishLab/semble and assigned a Trust Score of 100/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains MinishLab/semble?

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MinishLab/semble is maintained by MinishLab. The last recorded GitHub activity is from today, with 6 open issues.

Are there alternatives to semble?

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Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

Deploy semble to your cloud

Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.

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