ontomics
ontomics gives any coding agent instant knowledge of your codebase. One tool call instead of 19. ~20x fewer tokens.
https://github.com/user-attachments/assets/01afa8a0-1bc2-4686-94d7-965fef7610c3
Potencialize seu agente
O comando do próprio publicador. Não é um endpoint do PlugMCP.
Host a copy with our keys and logs.
npx -y @ontomics/[email protected]O Claude Code não tem link de instalação para um comando local. Copie o comando abaixo e execute-o em um terminal.
claude mcp add io.github.etiennechollet-ontomics -- npx -y @ontomics/ontomics@0.3.1Execute em um terminal.
{ "mcpServers": { "io.github.etiennechollet-ontomics": { "command": "npx", "args": [ "-y", "@ontomics/[email protected]" ] } }}claude_desktop_config.json
URL remota ou um comando na sua máquina? Como as duas instalações diferem
Rodar no PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
AbrirDo publicador
ontomics gives any coding agent instant knowledge of your codebase. One tool call instead of 19. ~20x fewer tokens.
https://github.com/user-attachments/assets/01afa8a0-1bc2-4686-94d7-965fef7610c3
Index your codebase's domain knowledge. 20x fewer tokens, 10x faster.
Visualization for the voxelmorph project -- a library for unsupervised learning in image registration
Tested with Claude Sonnet — same question, with and without ontomics.
"What does 'transform' mean in this codebase?" on voxelmorph (full transcript):
"What are the main domain concepts in this codebase?" on ScribblePrompt (full transcript):
Both conditions produced complete, correct answers. ontomics got there in one call.
Search tells you where a string appears. An LSP tells you where a symbol is defined and referenced. Neither answers: what are the domain concepts in this codebase? How do they relate? What naming conventions emerged? What changed in the domain vocabulary since last release? Which functions behave similarly, regardless of what they're named?
ontomics builds a semantic index of your project's domain — clustering related symbols into concepts, detecting naming conventions from usage frequency, resolving abbreviations, grouping functions by behavioral similarity, and tracking how the vocabulary evolves over time. That index can be exported as a portable artifact to bootstrap conventions in other repos.
Beyond naming and concepts, ontomics embeds raw function bodies using CodeRankEmbed (768-dim, contrastive code retrieval) and clusters them by behavioral similarity. This surfaces relationships that neither naming nor call graphs expose:
❯ What functions behave like spatial_transform()?
random_transform() nn/functional.py:352 0.80
spatial_transform() functional.py:596 0.69
random_transform() functional.py:1399 0.67
random_disp() nn/functional.py:275 0.65
integrate_disp() functional.py:764 0.65
compose() nn/functional.py:216 0.63
disp_to_trf() functional.py:343 0.62
The result also reveals that random_transform appears at two locations with different similarity scores — a sign of implementation duplication that concept-level search would miss entirely.
Install once, available in every project. No configuration needed — ontomics auto-detects the repo and indexes it on first run.
ontomics requires a git repository (.git/ directory). It will refuse to index home, root, or temp directories. To index a non-git directory, pass --force.
npm (macOS/Linux):
npm install -g @ontomics/ontomics
macOS (Homebrew):
brew install EtienneChollet/tap/ontomics
Shell installer (macOS/Linux):
curl --proto '=https' --tlsv1.2 -LsSf https://github.com/EtienneChollet/ontomics/releases/latest/download/ontomics-installer.sh | sh
From source:
git clone https://github.com/EtienneChollet/ontomics.git
cd ontomics
cargo build --release
Claude Code:
claude mcp add -s user ontomics -- ontomics
Codex:
codex mcp add ontomics -- ontomics
OpenClaw:
openclaw mcp set ontomics '{"command":"ontomics"}'
pi-coding-agent:
pi install npm:@ontomics/ontomics
Share with your team — drop an .mcp.json in your repo root:
{
"mcpServers": {
"ontomics": {
"command": "npx",
"args": ["-y", "@ontomics/ontomics", "--repo", "."]
}
}
}
Python, TypeScript, JavaScript, Rust. Auto-detected from file extensions.
ontomics runs a multi-stage pipeline entirely on your machine — no API keys required:
Both embedding models are downloaded once on first run and cached locally. The index lives at <repo>/.ontomics/index.db — subsequent startups load from cache and watch for file changes.
Configuration via .ontomics/config.toml in the repo root. All fields have sensible defaults. See SPEC.md for the full design contract.
Index your codebase's domain knowledge. 20x fewer tokens, 10x faster.
{ "mcpServers": { "io.github.etiennechollet-ontomics": { "command": "npx", "args": [ "-y", "@ontomics/[email protected]" ] } }}Ferramentas
Ainda não há lista de ferramentas. Servidores remotos recebem uma após a primeira verificação de saúde.
Perguntas frequentes
Copie nesta página a configuração stdio para Cursor, Claude Desktop, Claude Code ou VS Code. Ela usa a instalação do publicador, não um proxy do PlugMCP.
Este registro não lista nenhuma variável de ambiente obrigatória.
Ontomics roda localmente via stdio.
Última verificação: 2026-11-09. Index your codebase's domain knowledge. 20x fewer tokens, 10x faster.