Most AI agent workflows lose useful context between sessions, tools, and chats. The usual fixes are either too manual, like copying notes into docs, or too heavy, like setting up a database, vector store, or custom RAG stack. pumaDB gives agents a simple shared place to save and reuse notes, facts, preferences, project context, transcripts, task state, and other useful memory. No database setup, vector DB, or infrastructure to manage
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pumaDB is a durable memory layer for AI agents that eliminates the need for database setup, vector stores, or custom RAG infrastructure. It provides a simple shared place where agents can save and reuse notes, facts, preferences, project context, transcripts, task state, and other useful memory across sessions, tools, and chats. Instead of manually copying notes into documents or building complex infrastructure, developers connect via hosted MCP or a server-side API, store JSON rows, and review what their agents remember.
Connect pumaDB as a hosted MCP server using Streamable HTTP MCP endpoints. OAuth-ready and compatible with ChatGPT, Claude, Codex, OpenClaw, or any client supporting Streamable HTTP MCP. Setup takes seconds with a simple URL configuration.
For trusted server-side code, keep a named puma_live_* key in backend or serverless environments and call /v1 endpoints directly. This provides the same row operations as MCP but through HTTP routes for backends, Workers, CLIs, and scripts.
Store almost any small, durable JSON record: reusable operating instructions, project conventions, user preferences, research clippings, task state, and typed safe memory like code snippets and config examples. The consolidated remember MCP tool handles common memory types with inert safety metadata.
Account limits of 20 tables, 1,000 rows per table, and 25 MB total storage per account. Rate limits of 30 writes and 60 reads per minute per key. Automatic version history keeps the last 10 versions for 30 days with one-call restore. Natural edits let agents turn plain-language requests into filtered updates without duplicate rows.
"No database setup, vector DB, or infrastructure to manage."
pumaDB removes the entire infrastructure burden from agent memory management. While most solutions require either manual note-taking or complex database and vector store setup, pumaDB gives agents a simple shared place to save and reuse memory with just a URL connection. The built-in version history, rate limits, and natural edit capabilities make it production-ready without the operational overhead.
You're building multi-session AI agent workflows and want persistent memory without database management. You need agents to remember user preferences, project conventions, and task state across different tools and chats. You prefer a lightweight solution that works with existing MCP-compatible clients or server-side code, and you value built-in safety features like version history and rate limits over custom infrastructure.
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