#2424th of 52 in MCP servers for developers
semble
Local code search for coding agents, via MCP server or CLI
- Stars
- 6.3k
- License
- MIT
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Python
3 on 7 Apr 20266,255 on 20 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Semble indexes a local path or git URL with tree-sitter chunking, then ranks chunks by fusing static Model2Vec embeddings (potion-code-16M-v2) with BM25 using Reciprocal Rank Fusion. It runs on CPU and returns only matching snippets to agents such as Claude Code, Cursor, Codex and OpenCode. It ships as an MCP server with search and find_related tools, a CLI, a sub-agent installer and a Python library.
Who it is for: Developers giving Claude Code, Cursor or Codex fast local code search
Strengths
- Runs on CPU with no API keys or external services; model downloads once from Hugging Face
- Reports NDCG@10 of 0.855 over ~1,250 queries across 63 repos and 19 languages
- Searches several repos or git URLs as one corpus with incremental, cached indexes
- Interactive `semble install` configures MCP, AGENTS.md instructions or a sub-agent per detected agent
Weaknesses
- First run needs network access to fetch the embedding model unless SEMBLE_MODEL_NAME points locally
- Files over 1 MB and data files such as .json and .csv are skipped by default
- The ~99% token savings figure is the project's own benchmark against grep+read
- Retrieval only; it does not edit code or run commands
What it needs
- no GPU
- Needs uv, Hugging Face (first-run model download)
- Models: Model2Vec static embeddings (potion-code-16M-v2)
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| 2 | codegraphLocal code knowledge graph that coding agents query over MCP | 82 out of 100 |
| 3 | n8n-mcpMCP server exposing n8n node docs, templates and workflow management to AI assistants | 77 out of 100 |
| #4 | serenaMCP server giving coding agents symbol-level code search, editing and refactoring | 74 out of 100 |
| #5 | chrome-devtools-mcpMCP server that lets coding agents drive and debug a live Chrome | 72 out of 100 |