@ontomics/ontomics

ontomics

ontomics extracts domain knowledge from codebases to reduce LLM token consumption by 20x and time in agentic search by 10x. It gathers the concepts, naming conventions, and vocabulary embedded in your code and makes them queryable via MCP.

Benchmark

Tested with Claude Sonnet — same question, with and without ontomics.

"What does 'transform' mean in this codebase?" on voxelmorph (full transcript):

	With ontomics	Without
Tool calls	1	19
Tokens	~3.7k	~76k
Time	5s	1m 15s
Answer quality	Complete	Complete

"What are the main domain concepts in this codebase?" on ScribblePrompt (full transcript):

	With ontomics	Without
Tool calls	1	26
Tokens	~3.7k	~61.6k
Time	~5s	56s
Answer quality	Complete	Complete

Both conditions produced complete, correct answers. ontomics got there in one call.

What it does that search can't

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?

ontomics builds a semantic index of your project's domain — clustering related symbols into concepts, detecting naming conventions from usage frequency, resolving abbreviations, and tracking how the vocabulary evolves over time. That index can be exported as a portable artifact to bootstrap conventions in other repos.

Install

Install once, available in every project.

npm (macOS/Linux):

npm install -g @ontomics/ontomics
claude mcp add -s user ontomics -- ontomics

macOS (Homebrew):

brew install EtienneChollet/tap/ontomics
claude mcp add -s user ontomics -- ontomics

Shell installer (macOS/Linux):

curl --proto '=https' --tlsv1.2 -LsSf https://github.com/EtienneChollet/ontomics/releases/latest/download/ontomics-installer.sh | sh
claude mcp add -s user ontomics -- ontomics

From source:

git clone https://github.com/EtienneChollet/ontomics.git
cd ontomics
cargo build --release
claude mcp add -s user ontomics -- ontomics

No configuration needed. ontomics auto-detects the repo and indexes it on first run.

Supported languages

Python, TypeScript, JavaScript, Rust. Auto-detected from file extensions.

Tools

Tool	What it does
query_concept	Find all variants, related concepts, and occurrences of a term
locate_concept	Find the key signatures, classes, and files for a concept
describe_symbol	Get the signature, docstring, and relationships for a function or class
trace_concept	Trace how a concept flows through the codebase via call chains
list_concepts	List the top domain concepts by frequency
list_conventions	List all detected naming patterns (prefixes, suffixes, conversions)
list_entities	List code entities (classes, functions) filtered by concept, role, or kind
check_naming	Check an identifier against project conventions; suggests the canonical form
suggest_name	Generate an identifier name that fits the project's vocabulary
vocabulary_health	Measure convention coverage, naming consistency, and cluster cohesion
ontology_diff	Show new, changed, or removed domain concepts since a git ref
export_domain_pack	Export domain knowledge as portable YAML for use in other repos

Resources

Resource	What it does
ontomics://briefing	Session briefing: top conventions, abbreviations, key concepts, contrastive pairs, and vocabulary warnings. Also available via ontomics briefing CLI.

How it works

ontomics parses every file in your repo, extracts identifiers and docstrings, clusters related terms by embedding similarity, and detects naming conventions through frequency analysis. The index lives at <repo>/.ontomics/index.db — subsequent startups load from cache and watch for changes.

Configuration via .ontomics/config.toml in the repo root. All fields have sensible defaults. See SPEC.md for the full design contract.