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datamol

Self-hosted alternatives to datamol

5 self-hosted AI Skills apps to use instead, best rated first.

Top picks

  1. C

    claude-to-deerflow

    Launch

    claude-to-deerflow is an agent skill that lets an assistant send messages and questions to a running DeerFlow instance through its HTTP API. DeerFlow is an AI agent platform built on LangGraph that orchestrates sub-agents for research, code

    Self-hosted

  2. O

    open-notebook

    Launch

    open-notebook is an agent skill for organising research with Open Notebook, a self-hosted alternative to NotebookLM. It arranges sources, notes and AI conversations into research notebooks. Sources can be PDFs, web pages, audio, video and O

    Self-hosted

  3. R

    Reactive Resume

    Launch

    Reactive Resume is a free and open-source resume builder for writing resumes and cover letters, checking the work, and tracking job applications. You create a free account, import an existing resume or start from scratch, and see the finish

    Open sourceSelf-hosted

  4. S

    self-hosted-funnel-launch

    Launch

    Self-hosted funnel launch is an agent skill that takes a funnel from an empty install to published on infrastructure you control, using the Autonnel funnel builder, which is licensed Apache-2.0. The result covers a landing page, checkout, a

    Self-hosted

  5. G

    get-convex/convex-backend

    Launch

    Convex is an open-source reactive database for web app developers. It combines a database, a place to write server functions in pure TypeScript, and client libraries that keep the app's data live, so screens update as the data changes. Beca

    Self-hosted

About datamol

D

datamol

Pythonic wrapper around RDKit with simplified interface and sensible defaults

datamol is an agent skill for cheminformatics with datamol, a Pythonic wrapper around RDKit that offers a simpler interface and sensible defaults. It is preferred for standard drug discovery tasks, including SMILES parsing, standardisation and molecular operations. Its molecular objects are native RDKit molecule objects, so they work with the wider RDKit ecosystem. The skill also gives efficient parallelisation and modern input and output. The verified target is datamol 0.13.0, released on 9 September 2026, checked on Python 3.13 with RDKit 2026.03.6. Python 3.11 or newer and RDKit 2024.09 or newer are required. The 0.13 distribution includes runtime dependencies for SELFIES, visualisation, cloud, Excel and Parquet. The skill advises pinning the environment, because RDKit upgrades can change canonical representations and retained conformers. For that reason it suggests comparing chemical invariants rather than a fixed conformer count or an exact canonical string. Current API examples and verification limits are recorded in a review file. It is part of the k-dense-ai scientific agent skills repository on GitHub, which has about 49,600 stars.

View datamolAll AI Skills apps
Price
Free
Made by
k-dense-ai
Category
AI Skills
Website
github.com/k-dense-ai/scientific-agent-skills/datamol