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Deep research · AI agent

OpenScience: review, pricing, security and alternatives

OpenScience is an open-source AI agent published by Synthetic Sciences, in the deep research family. Provides an open-source AI workbench for scientific research with a command-line interface for research tasks. Its repository has 4,248 stars and its last commit is from October 20, 2026.

Open sourceSelf-hostableActively maintainedLow risk

What OpenScience does

OpenScience belongs to the deep research family: agents that search, read and cross-check dozens of sources to produce a sourced report. On our grid it ranks #6 of the 18 projects of this family listed in the directory.

You use it from: terminal (CLI). It can run on your own machine or server.

Who is OpenScience for?

It targets analysts, students and teams who must cross-check many sources to produce a reasoned summary. Typical tasks people give it:

  • write a sourced overview of a topic
  • compare products or competitors
  • prepare a technical or regulatory watch

It is a good candidate if you are comfortable in a terminal and your data must stay on your machines.

Access and human control

Its documentation does not detail the access granted to the agent: check the settings before connecting it to your accounts.

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

Run commands in a terminalRun commands in a terminal : 6 %6 %Read and edit filesRead and edit files : 28 %28 %Drive a web browserDrive a web browser : 22 %22 %Call online services and APIsCall online services and APIs : 56 %56 %
Share of the 18 agents in the family that have each access, according to their documentation. In orange, OpenScience's access.

OpenScience pricing

The code is free, under the Apache-2.0 licence.

Getting started with OpenScience

  1. Install it: the project ships as a Node.js package (install with npm, or run directly with npx). The exact command is in the repository README.
  2. Create an API key with the model provider and put it in an environment variable, never in a shared or versioned file.
  3. Give it a first playground with nothing at stake: a test folder, a secondary account or a throwaway project. Only open your real accounts once you have seen how it behaves.
  4. Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.

Security: risk level

An agent's report may cite misread or invented sources: check the links before reusing a figure.

Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.

Project activity and releases

Created on July 3, 2026, the synthetic-sciences/openscience repository has 4,248 stars, 534 forks and 0 open issues, with 1,207 commits in total. It received changes this month.

Over the last 52 weeks: 1,147 commits, an average of 22.1 per week.

Nov 2, : 0 · Nov 2, 2025Nov 2,Nov 9, : 0 · Nov 9, 2025Nov 16, : 0 · Nov 16, 2025Nov 23, : 0 · Nov 23, 2025Nov 30, : 0 · Nov 30, 2025Dec 7, : 0 · Dec 7, 2025Dec 14, : 0 · Dec 14, 2025Dec 21, : 0 · Dec 21, 2025Dec 28, : 0 · Dec 28, 2025Dec 28,Jan 4, : 0 · Jan 4, 2026Jan 11, : 0 · Jan 11, 2026Jan 18, : 0 · Jan 18, 2026Jan 25, : 0 · Jan 25, 2026Feb 1, : 0 · Feb 1, 2026Feb 8, : 0 · Feb 8, 2026Feb 15, : 0 · Feb 15, 2026Feb 22, : 0 · Feb 22, 2026Feb 22,Mar 1, : 0 · Mar 1, 2026Mar 8, : 0 · Mar 8, 2026Mar 15, : 0 · Mar 15, 2026Mar 22, : 0 · Mar 22, 2026Mar 29, : 0 · Mar 29, 2026Apr 5, : 0 · Apr 5, 2026Apr 12, : 0 · Apr 12, 2026Apr 19, : 0 · Apr 19, 2026Apr 19,Apr 26, : 0 · Apr 26, 2026May 3, : 0 · May 3, 2026May 10, : 0 · May 10, 2026May 17, : 0 · May 17, 2026May 24, : 0 · May 24, 2026May 31, : 0 · May 31, 2026Jun 7, : 0 · Jun 7, 2026Jun 14, : 0 · Jun 14, 2026Jun 14,Jun 21, : 0 · Jun 21, 2026Jun 28, : 0 · Jun 28, 2026Jul 5, : 6 · Jul 5, 2026Jul 12, : 220 · Jul 12, 2026Jul 19, : 52 · Jul 19, 2026Jul 26, : 10 · Jul 26, 2026Aug 2, : 72 · Aug 2, 2026Aug 9, : 33 · Aug 9, 2026Aug 9,Aug 16, : 14 · Aug 16, 2026Aug 23, : 36 · Aug 23, 2026Aug 30, : 146 · Aug 30, 2026Sep 6, : 86 · Sep 6, 2026Sep 13, : 92 · Sep 13, 2026Sep 20, : 136 · Sep 20, 2026Sep 27, : 104 · Sep 27, 2026Oct 4, : 100 · Oct 4, 2026Oct 4,Oct 11, : 16 · Oct 11, 2026Oct 18, : 5 · Oct 18, 2026Oct 25, : 19 · Oct 25, 2026Oct 25,
Commits per week on the main repository, last 52 weeks (GitHub API, checked October 25, 2026).

149 releases in total; 30 in the last twelve months. Latest release: v2.0.152, on October 18, 2026.

v2.0.134 · Sep 24, 2026v2.0.134Sep 24, 2026v2.0.133 · Sep 24, 2026v2.0.137 · Sep 25, 2026v2.0.136 · Sep 25, 2026v2.0.135 · Sep 25, 2026v2.0.139 · Sep 26, 2026v2.0.138 · Sep 26, 2026v2.0.140 · Sep 27, 2026v2.0.143 · Sep 28, 2026v2.0.142 · Sep 28, 2026v2.0.141 · Sep 28, 2026v2.0.146 · Sep 29, 2026v2.0.145 · Sep 29, 2026v2.0.144 · Sep 29, 2026v2.0.147 · Sep 30, 2026v2.0.150 · Oct 2, 2026v2.0.149 · Oct 2, 2026v2.0.148 · Oct 2, 2026v2.0.151 · Oct 5, 2026v2.0.152 · Oct 18, 2026v2.0.152Oct 18, 2026
The latest 20 releases published on GitHub (hover a point for details).

OpenScience vs other deep research

GitHub stars of the best-rated open-source projects in the deep research family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.

DeerFlowDeerFlow : 84.4K84.4KGPT ResearcherGPT Researcher : 30.3K30.3KOpen ScienceOpen Science : 5.4K5.4KFeynmanFeynman : 10K10KLocal Deep ResearchLocal Deep Research : 9.4K9.4KOpenScienceOpenScience : 4.2K4.2KLLM for ZoteroLLM for Zotero : 3.4K3.4KEvoScientistEvoScientist : 4.9K4.9K
Log scale; OpenScience in orange. Checked October 25, 2026.

OpenScience and other deep research at a glance

The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.

Quick comparison: deep research
AgentModelScoreStars or entry priceSelf-hostableHuman approval
OpenScienceopen source704.2K ★yes–
DeerFlowopen source8784.4K ★yes–
GPT Researcheropen source8030.3K ★yes–
Open Scienceopen source765.4K ★yes–
Feynmanopen source7410K ★yes–
Local Deep Researchopen source749.4K ★yes–
LLM for Zoteroopen source683.4K ★yes–
EvoScientistopen source654.9K ★––

How we rated it

Score: 70/100, computed only from public, verifiable data, with no subjective testing or partnership:

  • Adoption 20/40: 4,248 stars on a log scale (40 points from about 200,000).
  • Activity 30/30: last commit less than a month ago, 30 releases in six months, 1,147 commits in a year.
  • Framework 20/30: licence, default human approval, self-hosting, model choice and documentation site.

The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.

Verdict

OpenScience is a serious option; check the limitations below before granting it access.

Strengths

  • Very active development
  • Frequent releases (30 in a year)
  • Can run on your side: data under control
  • Permissive licence (Apache-2.0)

Frequently asked questions

Is OpenScience free?

The software is free (Apache-2.0 licence). You still pay for the model calls, unless you use a local model.

Is OpenScience safe?

Our risk level: low. Give it minimum rights and approve irreversible actions.

Which models does OpenScience use?

Its documentation does not specify the supported models.

Can OpenScience be installed on your own server?

Yes, from the synthetic-sciences/openscience repository. Data then stays with you, but security and updates are your job.

What are the alternatives to OpenScience?

In the same family: DeerFlow, GPT Researcher, Open Science, and Feynman.

OpenScience or DeerFlow: what is the difference?

Both belong to the deep research family. OpenScience has 4.2K stars against 84.4K for DeerFlow. The right choice mostly depends on the access you are willing to give it.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score