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Documentation Index

Fetch the complete documentation index at: https://docs.membase.so/llms.txt

Use this file to discover all available pages before exploring further.

Once your context is in Membase, there are three ways to use it: Chat in Dashboard for direct conversations with your knowledge base, Agent Retrieval by your connected agents, and Dashboard Exploration in either the Memory or Wiki views.

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Chat in Dashboard

The most direct way to interact with your knowledge base. Chat lets you ask questions and get answers grounded in your stored context, without going through an external agent. When stored context is relevant, it can search both your memory and your wiki and weave results into a single answer.
Chat with Memory
  • Ask anything: “What did we decide about the auth flow?”, “What’s my meeting schedule this week?”, “What does our deployment runbook say about rollbacks?”
  • Citations: Responses that use stored context link back to the exact memories and wiki documents they drew from
  • Graph panel: See how referenced items connect to each other
  • Session history: Pick up past conversations from the sidebar
Chat is available in the Chat tab of your dashboard. See Chat in Dashboard for details.

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Agent Retrieval

Your connected agents retrieve context from Membase when they need it. When past context or reference knowledge would improve the response, the agent can call search_memory (personal context) and search_wiki (factual knowledge) and combine the results before responding.
Your prompt
Set up a new API route for user profiles.
What happens behind the scenes
→ Agent calls search_memory: "project tech stack, API conventions"
  Found: "Uses Next.js with TypeScript"
  Found: "Prefers RESTful conventions with Zod validation"
  Found: "Supabase for auth"

→ Agent calls search_wiki: "user profile API schema, auth middleware"
  Found (doc): "User Profile Data Model" with fields, constraints, relations
  Found (doc): "Auth Middleware" with how to require a session on a route

→ Agent generates the route using the right stack, schema, and middleware.
This works across all connected agents. Context stored by Cursor is available to Claude, ChatGPT, and every other agent on your account. The same is true for wiki documents.
You don’t need to tell your agent to search. Agents call search_memory and search_wiki automatically whenever past context or reference knowledge would improve their response.

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Dashboard Exploration

You can explore your knowledge directly in the dashboard. Memory and Wiki are two separate tabs, each with its own views.
The Memories tab has two views for exploring personal context.
  • Graph View: Explore your knowledge as an interactive network of entities (people, concepts, tools, projects) and relationships. Click any node to see connected entities and related episodes.
  • Table View: Browse all memories in a structured list. Filter by source, project, and time period. Use the table search to text-filter the loaded memory list, then bulk-select rows to move them to a project or delete them.
For the full walkthrough, see Memory.

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Other Dashboard Tabs

Beyond Chat, Memory, and Wiki, the dashboard has a few more tabs:
TabPurpose
AgentsManage connected AI agents: connection status, last activity, add new agents
SourcesConnect app integrations (Gmail, Calendar, Slack, Obsidian, and more) and import past chat history
RecipesPre-built prompt templates that run directly in Chat, powered by your synced memories
SettingsTabbed settings page with Profile (name, role, interests, custom instructions, timezone; shared with agents via membase://profile) and Billing (current plan, usage including wiki document quota, and invoices)

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Next Steps

Bring Your Context

Import chat history and connect apps to enrich your knowledge base.

Memory

Explore and manage your memories.

Knowledge Wiki

Explore and manage your wiki documents.

Attached vs Universal

Understand why shared memory across agents matters.