All AI Tools in One Website: What Do You Actually Share?
Sites that list or combine AI tools differ from sites that share explicit work context across them. Understanding which you need avoids a confusing search.
Updated 5 min read
When people search for "all AI tools in one website," they are usually looking for one of three different things: a directory that lists many AI tools, a platform that lets you switch between several AI models in one interface, or a place that shares explicit work context — your instructions, project state and decisions — across the AI tools you use.
These are distinct products. Knowing which problem you are solving makes the search much shorter. A tool like fenbs is designed for the third: it keeps shared context outside any one AI app, so connected assistants read the same project record. For browsing what AI tools exist, AI tool directories serve that purpose.
What are AI tool directories?
An AI tool directory is a curated or crowdsourced list of AI products, organized by category — writing, image generation, coding, productivity and so on. Sites like There's An AI For That (theresanaiforthat.com) and Futurepedia (futurepedia.io) list hundreds or thousands of tools with brief descriptions.
These are useful when you want to discover tools for a new use case or compare options in a category you have not explored. They do not let you use multiple models in one place; they link out to each tool's own site. The directory itself shares nothing between the tools — it just lists them.
What are multi-model AI platforms?
Multi-model platforms give you access to multiple AI models from a single account and interface. Poe (poe.com, by Quora) lets you chat with ChatGPT, Claude, Gemini, Llama and others in one app. You.com lets you select different AI modes in one search interface. These are useful for comparing model responses side by side or avoiding multiple subscriptions.
What they do not do is share work context between models within the platform. You can switch from Claude to ChatGPT in the same Poe account, but the Claude conversation and the ChatGPT conversation are separate histories. The platform shares billing; it does not share your project brief.
What kinds of things are actually shared?
| Kind of site | What it shares | What it does not share |
|---|---|---|
| AI tool directory (e.g. theresanaiforthat.com) | Links and descriptions of tools in one place. | Nothing is shared between the tools themselves; you go to each tool separately. |
| Multi-model platform (e.g. Poe, You.com) | One account and billing across several models; sometimes side-by-side comparison. | Your project context, conversation history and instructions are not shared across models. |
| AI workspace with model switching (e.g. ChatGPT Projects, Claude Projects) | A system prompt and uploaded files within one provider's own models and conversations. | Context is not shared to other providers' models or tools outside that platform. |
| fenbs | Project context — tasks, decisions, rules, progress — readable by any connected AI over MCP. | fenbs does not access your chats or generate responses; it stores what you choose to record. |
The distinction is important because many articles and product descriptions blur these categories. "All your AI tools in one place" can mean a directory, a multi-model chat platform, or a context-sharing layer — all three are different products with different strengths.
What does shared work context actually mean?
Shared work context is the explicit record of your project: the goals, the tasks, the decisions that have been made, the rules that apply, and where the work currently stands. This is distinct from a model's memory of preferences or a conversation history. It is structured information you chose to record, that any connected tool can read.
Say a three-person design team uses Claude for writing, ChatGPT for research and GitHub Copilot for code. Each tool operates in its own session with its own history. The approved color palette, the client's constraints and the decision to use a particular component library are not visible to any tool unless someone re-explains them each session. Shared context solves that.
What does fenbs share across AI tools?
fenbs keeps the project record — tasks on a kanban board, Decisions and rules, Lessons learned, Where we left off, AI context notes and a shared glossary — and exposes it to connected AI apps over MCP (a standard way for an AI app to use an outside tool). A supported assistant reads the record at the start of a session and saves updates before it stops.
What fenbs does not share: it does not access your chat history on any AI tool, does not read your files unless you add them to the project, does not generate responses and does not train on your work. It stores what you explicitly record and shares it with the assistants you connect.
Share project context across the AI tools you use
Add your project to fenbs, record the decisions and rules that apply, and connect supported AI tools over MCP. Each connected assistant reads the same shared brief. Switch from writing to coding to research — the project context travels with you. Free for one person, no credit card.
Create a free accountFree for one person · No credit card · Works with Claude, ChatGPT, Cursor and more
When do you need shared context rather than a directory or platform?
You need shared context when the same project spans more than one AI tool or session. If you use Claude today and ChatGPT tomorrow on the same project, and you want tomorrow's assistant to know what was decided today, that requires a shared record — not just access to both tools.
You need it when a team uses different AI tools: a designer using Gemini, a developer using Claude Code and a project manager using ChatGPT should all be working from the same project decisions and status, not independent chat histories. The AI memory for teams guide covers this scenario in more depth.
How to do this with fenbs
- Create a free account and add a project. You can start with a personal board and move to a team board when colleagues need access.
- Add the current tasks and write the decisions and rules for this project. Keep the first version short — what does the next session need to know?
- Connect supported assistants from Integrations. The connection uses browser-based OAuth sign-in; no tokens to paste.
- Ask each connected assistant to read the project context at session start. It reads Rules first, then Where we left off and In progress tasks.
- Before ending a session, ask the assistant to save progress so the record stays current for the next session on any supported tool.
When a directory or multi-model platform is enough
If you are exploring what AI tools exist, an AI tool directory is the right starting point. If you want to try several models without multiple subscriptions, a multi-model platform like Poe is useful. fenbs is for ongoing work where the project record needs to be consistent across sessions, tools and people — not for discovering new tools or running one-off comparisons.