Skip to content

MemoryPapr

Papr

Memory graph and retrieval layer that gives AI agents long-term context.

Category
Memory
Pricing
FREEMIUM
Source
Open core
Hosting
Hybrid
Platforms
WebAPI
Models
Model-agnostic
Verified
Jul 5, 2026

Papr is a memory layer for AI agents that turns unstructured data—documents, conversations, and logs—into a searchable knowledge graph with long-term recall. It offers graph-aware retrieval, automatic chat-memory compression, and TypeScript and Python SDKs, exposed through a REST API and a managed cloud dashboard. Its papr-2 model reports sub-150ms cached retrieval, and the core can be self-hosted.

Capabilities 4

What it actually does — grouped by capability family.

  • Agent memory (primary capability)
  • Knowledge graph (primary capability)
  • Vector search (secondary capability)
  • RAG pipeline (secondary capability)

Pros & cons

  • Open-source AGPL-3.0 core
  • TypeScript and Python SDKs
  • Managed cloud or self-hostable
  • Automatic chat-memory compression
  • Newer, smaller ecosystem
  • Memory-only scope
  • AGPL may deter some commercial use

Tags

Alternatives to Papr (4)

View all Memory →
  • View mem0 details
    MemoryFREEMIUMOpen core

    mem0

    Mem0

    Long-term memory layer for AI agents. Self-hostable.

    Persistent memory store + retrieval pipeline for agent applications. Handles per-user/per-session/per-agent scope cleanly; pairs with OpenAI, Anthropic, and local models.

    Quick to adopt, broad framework integrations
    Weaker on temporal/state-change queries
    • memory
    • agents
    • rag
    • self-hosted
    Open
  • View Zep details
    MemoryFREEMIUM

    Zep

    Zep

    Temporal knowledge-graph memory for AI agents.

    Memory layer that gives agents long-term context by building a temporal knowledge graph from chat history and business data, tracking how facts evolve over time. It's powered by Graphiti, Zep's Apache-2.0 open-source temporal graph engine, with Zep Cloud offering a managed, credit-based service on top. Used to keep agent context relevant as conversations and data grow.

    Open-source Graphiti engine (Apache-2.0)
    Graph approach has learning curve
    • memory
    • agents
    • knowledge-graph
    • temporal
    • +1
    Open
  • View Supermemory details
    MemoryFREEMIUMOpen core

    Supermemory

    Supermemory

    Memory API that gives any AI agent long-term recall.

    Supermemory is a memory and context engine for AI apps. It ingests documents, chat histories, and connector data (Drive, Gmail, Notion), turns them into a searchable store, and serves relevant context back to agents over a single API. It works with any model and ships an MCP server alongside official SDKs.

    MIT-licensed, self-host or managed
    Younger project, evolving API
    • agent-memory
    • rag
    • long-term-memory
    Open
  • View Graphlit details
    MemoryFREEMIUM

    Graphlit

    Graphlit

    One API for AI agent memory: ingest, extract, store, retrieve.

    A cloud-native platform that gives AI agents semantic memory and operational context through a single API. It ingests documents, audio, video, and web pages, extracts entities and relationships, and handles storage and retrieval so you don't assemble the RAG pipeline yourself. Integrates with frontier models from OpenAI, Anthropic, and Google for extraction.

    One API for ingest, extract, store, retrieve
    More infra/overhead than plain RAG
    • memory
    • context
    • rag
    • knowledge-graph
    Open
Open Papr