semble
Fast and Accurate Code Search for Agents. Uses 99% fewer tokens than grep+read
- 6.3k stars
- 281 forks
- 7 open issues
- Language: Python
- License: MIT
- updated
Install
local · uvx (python)claude mcp add semble -- uvx semble{
"mcpServers": {
"semble": {
"command": "uvx",
"args": ["semble"]
}
}
}{
"mcpServers": {
"semble": {
"command": "uvx",
"args": ["semble"]
}
}
}- Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
- Replace any <placeholder> values with your API keys or paths.
- 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.
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.
MCP Servers overview
What people ask about semble
What is MinishLab/semble?
MinishLab/semble is mcp servers for the Claude AI ecosystem. Fast and Accurate Code Search for Agents. Uses 99% fewer tokens than grep+read It has 6.3k GitHub stars and its last recorded update is dated 2026-10-16.
How do I install semble?
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?
Our security agent has analyzed MinishLab/semble and assigned a Trust Score of 92/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains MinishLab/semble?
MinishLab/semble is maintained by MinishLab. The last recorded GitHub activity is dated 2026-10-16, with 7 open issues.
Are there alternatives to semble?
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.