See it in action
Without MemoryPlugin:

How it works behind the scenes
When chat history context is requested, MemoryPlugin doesn’t dump raw chunks into your prompt. It retrieves and condenses:- Query understanding. Your query is analyzed to generate several search variations and extract any date filters (like “last month”).
- Hybrid search. Semantic and keyword searches run in parallel across your history.
- Reranking. Results are reranked by relevance to your specific query.
- Context expansion. For each match, surrounding messages are pulled in for complete context.
- Summarization. The expanded context is summarized to fit your token budget. Tens of thousands of tokens of raw conversation might come back as a few hundred tokens of relevant summary.
Browser Extension
The Browser Extension works across all major AI platforms. Supported platforms: ChatGPT, Claude, Gemini, Google AI Studio, Grok, Poe, DeepSeek, Qwen, and more. How it works:- Runs one round of retrieval per message
- Injects automatically (context on every message) or manually (only when you click the MemoryPlugin button)
- Uses the token limits configured in extension settings
Chat History Memory is separate from Regular Memory in the browser extension.
They use different systems and different buttons.
Remote MCP Server (more control)
The Remote MCP Server is the most flexible way to use Chat History Memory. Instead of a marker, MCP clients call a real tool namedrecall_chat_history.
Supported platforms: Claude Desktop, Claude Web, Claude Mobile, Mistral AI, Cursor, Continue, and other MCP-compatible clients.
What recall_chat_history can do:
- Multiple rounds of retrieval in a single conversation, not just one per message
- Parallel queries. Send up to 15 queries that all run at once, each hitting a topic from a different angle (timeline, people, decisions, outcomes)
- Per-query token budget.
maxTokensdefaults to 600, capped at 2000; 300 to 1000 is the useful range. More tokens means richer detail but a bigger chunk of the conversation window - Date bounds. Constrain a query with
before/afterusing ISO dates like2025-01-15. Bare dates are interpreted in UTC and inclusive on both ends - Speed or quality mode. Defaults to speed; ask for quality mode for slower but more thorough recall on hard or ambiguous queries
Best experience: Claude (Desktop, Web, or Mobile) and Mistral AI. These
models are good at agentic tool use and at folding retrieved context into an
answer naturally.
Controlling what gets added
Use exclusions to keep specific chats out of context: sensitive conversations, off-topic chats, or outdated discussions. When you exclude a chat, its content is deleted and it won’t be re-imported on future uploads or syncs. A placeholder remains so it isn’t re-processed.Searching and analyzing your history
You can also search and question your history in the dashboard:Search your history
Find specific discussions by topic, keyword, or timeframe with hybrid search.Go to Dashboard → Search
Ask questions
Get answers synthesized from your history, with citations, using the unified Ask tool.Go to Ask
Tips for best results
Be specific in your instructions
Be specific in your instructions
With the MCP server, tell the AI exactly what to recall. Instead of “use MemoryPlugin,” say “recall context about my React projects” or “recall my cooking preferences.”
Use parallel queries for broad topics
Use parallel queries for broad topics
For thorough coverage, ask for several parallel queries at once (up to 15): “recall this from a few angles: technical details, design decisions, and user feedback.”
Match the depth to the task
Match the depth to the task
Sometimes you want a lot of context (many queries, higher token budgets), sometimes none. Both are fine, and depth helps even for creative writing or documentation where past context keeps things consistent.
Control timing
Control timing
Tell the AI when to recall: at the start of every conversation, only when you mention it, or just for certain kinds of questions.
Limitations
Doesn't track how facts change over time
Doesn't track how facts change over time
Chat History doesn’t yet reason about how a fact evolved. If you struggled with a topic in March but understood it by June, the AI may not know which is current. We’re working on this.
Results vary by model
Results vary by model
How well the context lands depends on how good your AI model is at using retrieved context. Some models incorporate it better than others.
Troubleshooting
Context not appearing
Context not appearing
Try:
- Confirm the Browser Extension or Remote MCP Server is installed and signed in
- For the browser extension, check that Chat History Recall is enabled in settings
- For MCP, explicitly ask the AI to use
recall_chat_history - Confirm you’ve uploaded and processed chat history
Irrelevant context
Irrelevant context
Try:
- Be more specific in your prompt or instructions
- Exclude irrelevant chats from the Chats tab
- For MCP, ask the AI to use fewer tokens or narrower queries
Next Steps
View Dashboard
Search your history, ask questions, and manage your conversations
Browser Extension Setup
Install and configure the Browser Extension
Remote MCP Server Setup
Set up the Remote MCP Server for Claude Desktop and other clients
Back to Introduction
Review what Chat History Memory is and why it matters