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ontomics MCP server

by EtienneChollet·io.github.EtienneChollet/ontomics·v0.3.1·43 stars
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Index your codebase's domain knowledge. 20x fewer tokens, 10x faster.

C66/100grade C
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Safety scan
C66/100

full report

Adoption
Growing

43 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

ontomics tools

No tool declarations could be read from the package source. They show once the server is installed.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

2 medium
  • Code scan7 source files scanned15/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 164 days ago8/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Findings (2)

  • mediumnpm install lifecycle script presentinstall.script
  • mediumnpm install lifecycle script presentinstall.script
    package.json: …check": "prettier --check **/*.js", "postinstall": "node ./install.js" }, "supportedPl…
Overall 66/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How ontomics compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
66/100
higher than 23% of 48,255 servers
GitHub stars
43
more than 93% of 28,688 servers

Install ontomics in Claude Code, Cursor or VS Code

Runs npx -y @ontomics/ontomics on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add ontomics -- npx -y @ontomics/ontomics
Add to Cursor

What the publisher says

From the ontomics repository's README, as published. We do not edit it. Read it on GitHub

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

Visualization for the voxelmorph project -- a library for unsupervised learning in image registration

Benchmark

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.

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? 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.

Behavioral similarity

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

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

ontomics: common questions

Is ontomics MCP server safe?
With care: it is graded C, so read the findings first (66/100). Read the ontomics safety report
How do I install ontomics?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does ontomics need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is ontomics maintained?
The last commit was 201 days ago (2026-04-17). The latest release is v0.3.1.
What can I use instead of ontomics?
Servers from other publishers that do the same job: Codebase Memory MCP server, Trace MCP server and Honcho MCP server.
How does ontomics compare with other MCP servers?
safety score 66/100 (higher than 23% of 48,255 servers); github stars 43 (more than 93% of 28,688 servers). Full comparison.

Alternatives to ontomics

Same job from other publishers: the closest match first, then the best rated.

  • Codebase Memory
    Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
    C
  • Trace
    Code graph MCP: 81 languages, 91 frameworks, 72.7% fewer PR-review tokens, comprehension at parity
    A
  • Honcho
    Memory that reasons: continual learning for stateful agents. Better context, fewer tokens.
    A