Works with Claude, ChatGPT, Copilot, and Gemini agents

A workspace built for your AI agents

Give your AI agents shared knowledge and persistent memory. Connect your sources once, then let agents read, save, and update context across every run.

7-day free trial · start for free · cancel any time

The Context Link dashboard with connected sources and lens tabs

01 / Why Context Link

Persistent memory
across agent runs

Agents forget at the end of every session. Memories let AI save outputs under any /slash route, then retrieve them on the next run.

One knowledge base
every agent shares

Connect your sources once. Every agent (research, support, sales) pulls from the same approved set via semantic search.

Read and write,
without DIY RAG

Skip the embedding pipeline and vector DB. Agents get retrieval and a writable workspace through a simple URL or skill.

Try for Free 7-day free trial · start for free · cancel any time

02 / Works with

AI's: Claude
ChatGPT
Google Gemini
Microsoft Copilot
Sources: Google Docs
Google Drive
Notion
Basecamp Basecamp
OneDrive
Monday
Custom Custom
Types:
Websites Websites
Files Files
Email Email
Memory Memory

*Don't see a pre-built connection? Download the custom-connections skill and Claude builds it for you. If Claude can read it, you can push it to Context Link.

03 / What it does

Connect your agent's sources

Link Notion, Google Docs, Google Drive, OneDrive, Basecamp, Monday.com, email inboxes, websites, uploaded file stacks, and custom connections. Your agents pull from the same approved set you already use. No migration, no parallel knowledge base. If Claude can read it, you can push it to Context Link.

Semantic retrieval for every tool call

Agents call 'get context on [topic]' and Context Link returns the most relevant snippets by meaning. Clean markdown that fits inside the context window, not bulk-loaded chunks that crowd out the actual work.

Memories that compound across runs

Ask the agent to save this to /research-notes or update /customer-profile with these findings. Future runs fetch and refine those files, so each pass builds on the last instead of starting from scratch.

Model-agnostic, across every agent

One setup works with Claude agents, ChatGPT agents, Copilot, Gemini, and custom workflows via API. Switch models or run multiple agents in parallel without rebuilding your context layer.

04 / In action

Integrates with the AI you already use

Getting context in ChatGPT
ChatGPT Get Context · ChatGPT See the official app →
Getting context in Claude
Claude Get Context · Claude See the doc →

05 / Tools & skills

Skills your AI already knows how to call

Install once and your AI gets a vocabulary for your business: pull source-backed context, ask for a cited answer, or save a decision every other AI tool will read next time.

Tools & skills

Available in ChatGPT, Claude, Claude Code, and any MCP-aware agent.

get-context

Pulls source-backed context on a topic into the AI's working context.

When: “get context on…”

ask-question

One concise answer with citations, grounded in your sources.

When: “ask my docs…”

save-memory

Distills the conversation into a reference doc and saves it.

When: “save this as…”

update-memory

Fetches a saved memory, merges in what's new, saves it back.

When: “update… with…”

custom-connections

The AI becomes the fetcher: pushes any service's data into your knowledge base.

When: building a custom source

06 / Industries

Context Link works with your kind of business.

Whatever you run, it probably lives in a variety of places. Connect them once, and Give AI a single way to talk to all of it.

E-commerce business
your E-commerce business

Connect the support inbox, brand book, catalogue and help centre once, and AI gets a single place to ask your whole e-commerce business. From ChatGPT or Claude, ask what customers keep contacting support about, what you currently say about pricing, or how a product is described, and get source-backed answers instead of pasted-in context. When you settle something, like a returns policy or a brand rule, save it as a Memory so every AI tool reads the latest version.

08 / Workflows

Workflow

See exactly what each agent used and improve over time

Every retrieval and save is logged: which sources were pulled, what was returned, and when. Review agent quality, spot content gaps, and re-sync when something's drifted.

Agent response logs showing retrieved sources

Workflow

Control what agents can see down to the page

Choose exactly which Notion pages, Google Docs, folders, and site sections are indexed. Admins manage org-level sources for the whole agent fleet; individuals add personal connections that stay private.

Source management for AI agents

Tune retrieval per agent

Modes for each agent's job

Create named profiles like 'research-agent' or 'support-agent' that re-weight which sources matter most. The same knowledge base serves a research agent and a support agent differently. Switch via a `?mode=X` parameter on any query.

Modes walkthrough for AI agents

09 / Across your team

Share context across your team

Stop pasting the same docs into every chat. Connect your sources once, and every teammate's AI pulls the latest context from the same place — consistently, with citations, every time.

Your team's AIs

ChatGPT
Ellie
ChatGPT
Claude
Joel
Claude
agent 004
Marketing
agent 004
session
Deep research
session

One connected knowledge base

Services page
Blog posts
Proposal template
Pricing list 2026
Legals policy
Case studies
5-Step Growth Playbook
About page
Brand guidelines
Onboarding flow
Quarterly review
+
Keyword tracker
+
New customer checklist
+
Brand voice notes

Ready when you are

Ready to give your AI agents a shared workspace?

7-day free trial · start for free · cancel any time

FAQ

Frequently Asked Questions

What is an AI agent workspace?

An AI agent workspace is a shared layer where AI agents read context from your connected knowledge sources and write outputs they can retrieve later. Instead of every agent run starting from zero, agents pull from a single approved set of sources (Notion, Google Docs, email, websites, and more) and save reusable Memories under /slash routes. The result: agents that build on prior work instead of repeating it.

How does this give AI agents persistent memory?

Memories are canonical documents AI saves under any /slash route, for example, /research-notes, /customer-profile, or /roadmap. An agent can save its output at the end of a run by asking to "save this to /route-name", then a future run can fetch and update that file. Memories live alongside your synced sources but stay separate, so agents can iterate on their own files without touching your originals.

Can multiple agents share the same workspace?

Yes. Org accounts let admins connect company sources once, then every agent (and every teammate) queries the same pool via API, ChatGPT connector, or Claude skill. Memories are visible across sessions and agents, so a research agent can save findings that a writing agent picks up later. Modes let you re-weight the same sources per agent role without duplicating content.

Which agent frameworks does Context Link work with?

Context Link is model-agnostic. It runs inside Claude (via skills), ChatGPT (via the app connector), Copilot, and Gemini, and exposes a REST API for custom agent frameworks. Anything that can make an HTTPS call can fetch context or save Memories, including Zapier, Make, cron jobs, and your own agent stack.

How is this different from native ChatGPT or Claude memory?

Native memories load a small set of preference snippets into the context window at the start of every session, whether relevant or not. Context Link retrieves selectively: ask about pricing and you get 3 chunks from your pricing doc and 2 from a Notion page, not your whole memory dump. Agents can also save unlimited Memories under any /slash route and retrieve only the right one for the task at hand. The context window stays focused, and the workspace scales to thousands of files.

Can agents get a direct answer instead of raw snippets?

Yes. Alongside "get context on [topic]," agents can invoke the Ask Question skill: /ask-question [question] or natural language like "ask Context Link what our refund policy is." Same retrieval under the hood, but a small fast LLM composes one grounded paragraph with numbered citations back to your sources. Available on Pro and ideal when an agent needs a direct answer rather than source material to reason over.