How to Store AI Chat Context for Agents: Step-by-Step Guide

Handing conversation context from one AI tool to another should not require copying and pasting chat logs into Slack messages or shared documents. This step-by-step guide shows you how to store AI chat context properly using AirClippy's AI Context Vault so any agent can pick up where you left off. ## Why Store AI Chat Context? AI agents work best with full conversation history. When you start a new session without prior context, the agent lacks project background, previous decisions, and established tone. Storing chat context centrally solves this. Benefits of structured context storage: - Agents continue conversations without re-explaining everything - Multiple agents can access the same thread with controlled permissions - Context expires automatically so stale data does not accumulate - Messages stay in a standard format every API understands ## Prerequisites Before you begin, you need: - An AirClippy account (sign in at airclippy.com/login) - Access to AI Context Vault at airclippy.com/ai-context - Your chat history in a messages array format ## Step 1: Sign In and Open the Vault Navigate to airclippy.com/ai-context and sign in with your AirClippy account. The dashboard shows three tabs: Contexts, API keys, and Save context. The free tier includes 50 private contexts, 10 API keys, and a 7-day default TTL for each saved context. ## Step 2: Create an API Key Go to the API keys tab and click Generate key. Give your key a descriptive name like "Cursor Agent" or "CI Pipeline." Copy the key immediately — it is shown only once. The key format is actx_sk_… and is used as: Authorization: Bearer actx_sk_YOUR_KEY Paste the key into the Active API key field at the top of the dashboard. It is stored only in your browser's local storage. ## Step 3: Prepare Your Chat Context Format your conversation as a JSON object with messages and optional metadata: { "messages": [ { "role": "system", "content": "You are helping with the AirClippy project." }, { "role": "user", "content": "We decided to use Firestore for context storage." }, { "role": "assistant", "content": "Got it. I'll use Firestore with scoped share tokens." } ], "metadata": { "source": "cursor", "project": "airclippy", "tags": ["architecture", "decisions"] } } Each message needs a role (system, user, or assistant) and content string. Metadata is optional but helps organize contexts across projects. ## Step 4: Save the Context Switch to the Save context tab. Enter a descriptive title like "Architecture decisions — March 2026." Paste your JSON into the editor and click Save private context. The vault stores up to 500 messages and 512 KB per context. Contexts expire after 7 days by default (configurable up to 30 days via the API). ## Step 5: Verify Your Saved Context Go to the Contexts tab and click your saved context. You will see the full message array, metadata, message count, and expiry date. Confirm everything looks correct before sharing. ## Step 6: Share With an Agent Select your context and scroll to the Share with an agent section. Choose scopes: - **read** only: Agent can pull context but not modify it - **append**: Agent can add new messages to the thread - **write**: Agent can fully update the context Set an expiry in hours (default 24) and click Mint share token. Copy the token — it is shown once. Your agent accesses context at: GET https://airclippy.com/api/v1/share/actx_sh_YOUR_TOKEN ## Step 7: Inject Context Into Your Agent Here is a minimal example for a Node.js agent: const res = await fetch("https://airclippy.com/api/v1/share/" + process.env.AIRCLIPPY_SHARE); const { context } = await res.json(); const completion = await openai.chat.completions.create({ model: "gpt-4o-mini", messages: context.messages, }); The agent receives the full conversation and continues from the last message. ## Step 8: Append Agent Replies If you granted append scope, the agent can write back: curl -X PATCH https://airclippy.com/api/v1/share/actx_sh_YOUR_TOKEN \ -H "Content-Type: application/json" \ -d '{ "append": true, "messages": [ { "role": "assistant", "content": "Implemented Firestore storage. Next: add rate limiting." } ] }' This keeps the context thread growing as agents work. ## Best Practices - **Use descriptive titles**: "Q1 roadmap decisions" beats "Untitled context" - **Tag with metadata**: Include source tool, project name, and relevant tags - **Limit share scope**: Grant only the permissions the agent needs - **Set short expiry for sensitive context**: 24 hours is enough for most handoffs - **Delete when done**: Remove contexts you no longer need - **Revoke unused API keys**: Keep your key list clean in the dashboard ## Troubleshooting **"Not signed in"**: Sign in at airclippy.com/login first. **"Create or paste an API key first"**: Generate a key in the API keys tab and paste it in the Active API key field. **JSON parse error**: Validate your JSON structure. Every message needs role and content fields. **Context expired**: Re-save the context or increase ttlDays via the API (max 30 days). ## Next Steps Read the full API reference at airclippy.com/ai-context/docs for programmatic context management, batch operations, and integration patterns. Storing AI chat context in a vault transforms fragile copy-paste handoffs into reliable, scoped, agent-ready workflows. Save your first context today and experience seamless agent continuity.