Personal assistants · AI agent
Everywhere: review, pricing, security and alternatives
Everywhere is an open-source AI agent published by Sylinko, in the personal assistants family. A desktop assistant that uses the current application's on-screen context, multiple language models, and MCP tools to help with tasks. Its repository has 6,331 stars and its last commit is from October 22, 2026.
What Everywhere does
Everywhere belongs to the personal assistants family: general-purpose agents, often self-hosted and driven from a messaging app, that act for you on your files, accounts and services. On our grid it ranks #26 of the 46 projects of this family listed in the directory.
You use it from: desktop app. Usable models: DeepSeek, GPT (OpenAI), Claude (Anthropic), and Gemini (Google). It can run on your own machine or server.
Who is Everywhere for?
It targets individuals and freelancers who want an assistant able to act for them day to day, often from a messaging app. Typical tasks people give it:
- sort e-mail and draft replies
- manage a calendar and reminders
- look up information and summarise it
- run small recurring tasks
It is a good candidate if 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.
Everywhere pricing
The code is public but the repository declares no licence: reuse is not formally allowed. The real cost comes from model calls: each loop step sends the whole context back to the model, and a task of several dozen steps can cost far more than a single question. The LLM price calculator estimates it for the chosen model.
Getting started with Everywhere
- Install it by following the repository README (project written in C#).
- Create an API key with the model provider and put it in an environment variable, never in a shared or versioned file.
- 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.
- Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.
Security: risk level
A personal assistant often combines access to private data, reading outside content and sending messages: the combination that enables data leaks through prompt injection.
Points found for Everywhere:
- No licence: legally shaky for company use.
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 April 23, 2025, the Sylinko/Everywhere repository has 6,331 stars, 392 forks and 24 open issues, with 2,049 commits in total. It received changes this month.
Over the last 52 weeks: 1,510 commits, an average of 29 per week.
88 releases in total; 4 in the last twelve months. Latest release: v0.8.2, on September 16, 2026.
Everywhere vs other personal assistants
GitHub stars of the best-rated open-source projects in the personal assistants family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.
Everywhere and other personal assistants 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.
| Agent | Model | Score | Stars or entry price | Self-hostable | Human approval |
|---|---|---|---|---|---|
| Everywhere | open source | 64 | 6.3K ★ | yes | – |
| OpenClaw | open source | 95 | 392.9K ★ | yes | – |
| Hermes Agent | open source | 90 | 256.7K ★ | yes | – |
| nanobot | open source | 87 | 49.3K ★ | yes | – |
| CowAgent | open source | 87 | 47.6K ★ | yes | – |
| QwenPaw | open source | 86 | 36K ★ | yes | – |
| ZeroClaw | open source | 85 | 33K ★ | yes | – |
| OpenHuman | open source | 82 | 42.3K ★ | yes | – |
How we rated it
Score: 64/100, computed only from public, verifiable data, with no subjective testing or partnership:
- Adoption 22/40: 6,331 stars on a log scale (40 points from about 200,000).
- Activity 27/30: last commit less than a month ago, 4 releases in six months, 1,510 commits in a year.
- Framework 15/30: 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
Everywhere is a serious option; check the limitations below before granting it access.
Strengths
- Very active development
- Can run on your side: data under control
- Free choice of model
Limitations
- No licence declared
Alternatives
Learn more
Frequently asked questions
Is Everywhere free?
The software is public, with no declared licence. You still pay for the model calls, unless you use a local model.
Is Everywhere safe?
Our risk level: mid. Points found: no licence. Give it minimum rights and approve irreversible actions.
Which models does Everywhere use?
According to its documentation: DeepSeek, GPT (OpenAI), Claude (Anthropic), and Gemini (Google).
Can Everywhere be installed on your own server?
Yes, from the Sylinko/Everywhere repository. Data then stays with you, but security and updates are your job.
What are the alternatives to Everywhere?
In the same family: OpenClaw, Hermes Agent, nanobot, and CowAgent.
Everywhere or OpenClaw: what is the difference?
Both belong to the personal assistants family. Everywhere has 6.3K stars against 392.9K for OpenClaw. 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