Semble: Code Search for AI Agents Using 98% Fewer Tokens Than grep+read

Semble is a fast, token-efficient code search library built specifically for AI coding agents like Claude Code, Cursor, Codex, and OpenCode. It returns relevant code snippets from natural language or code queries, using ~98% fewer tokens than the typical grep+read fallback approach.
How It Works
Semble combines static Model2Vec embeddings (using their own potion-code-16M model) with BM25, fused via RRF and reranked with code-aware signals. All computation runs on CPU — no GPU, no API keys, no external services. Indexing an average repo takes ~250ms, and queries complete in ~1.5ms on CPU.
Key Features
- Token-efficient: 98% fewer tokens than grep+read — returns only the relevant chunks.
- Fast: ~250ms to index a typical repo, ~1.5ms per query (very large repos may take longer).
- Accurate: 0.854 NDCG@10 on their benchmark of ~1250 query/document pairs across 63 repos and 19 languages — 99% of the best transformer setup (137M parameters) at ~200x faster indexing and ~10x faster queries.
- Zero config: No API keys, GPU, or external services required.
- MCP server: Drop-in for Claude Code, Cursor, Codex, OpenCode, and any MCP-compatible agent.
- Local and remote: Pass a local path or a git URL. Indexes are cached per session and auto-updated on file changes.
Installation and Setup
MCP server (recommended for agents)
Requires uv to be installed. For Claude Code:
claude mcp add semble -s user -- uvx --from "semble[mcp]" semble
For Codex, add to ~/.codex/config.toml:
[mcp_servers.semble] command = "uvx" args = ["--from", "semble[mcp]", "semble"]
For OpenCode, add to ~/.opencode/config.json:
{
"mcp": {
"semble": {
"type": "local",
"command": ["uvx", "--from", "semble[mcp]", "semble"]
}
}
}For Cursor, add to ~/.cursor/mcp.json or .cursor/mcp.json:
{
"mcpServers": {
"semble": {
"command": "uvx",
"args": ["--from", "semble[mcp]", "semble"]
}
}
}Bash integration (alternative)
Install with pip or uv, then add the code search snippet to AGENTS.md or CLAUDE.md:
pip install semble uv tool install semble
Then in AGENTS.md:
## Code Search Use `semble search` to find code by describing what it does or naming a symbol/identifier, instead of grep: ```bash semble search "authentication flow" ./my-project ```
MCP Tools
The MCP server exposes two tools:
search— Search a codebase with a natural-language or code query. Passrepoas a local directory path or an https:// git URL.find_related— Given a file path and line number, return chunks semantically similar to the code at that location.
📖 Read the full source: HN AI Agents
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