pumaDB vs Spider Cloud

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-10
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At a glance

DimensionpumaDBSpider Cloud
Core UsePersistent memory / structured JSON storage for AI agentsWeb crawling & scraping for AI agents (RAG, LLMs)
Key FeatureMCP + REST API, automatic version history, natural language editRust engine, Browser AI commands (Act/Extract/Observe), 1K+ scraper catalog
IntegrationsChatGPT, Claude, Codex, OpenClawLangChain, LlamaIndex, CrewAI, FlowiseAI, AutoGen, S3, GCS, Supabase
Best ForLightweight agent memory and handoffHigh-volume, real-time web data extraction
LimitationsNo relational DB, 25MB total, no browser-side usageNot for simple one-off tasks or extreme anti-bot

Choose Spider Cloud if your AI agent needs fresh, structured web data at scale with low cost and rich integrations. Choose pumaDB if your priority is simple, schema-less persistent memory for agent state, handoffs, and notes without database overhead. They solve different problems: one feeds data in, the other stores it.

Try pumaDBTry Spider Cloud
pumaDB
pumaDB

Hosted MCP and REST memory that keeps AI agent context consistent across ChatGPT, Claude, Codex, and your own agents.

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Spider Cloud
Spider Cloud

Spider Cloud is a scraping, crawling, and search API that returns live pages as markdown or JSON for agents and RAG pipelines.

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Pricing
Freemium
Freemium
Plans
$0/mo
$99/month
Custom
$1/GB + $0.0001/CPU-min
From $6/mo
From $40/mo
Custom
Popularity
3 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
APIWeb
WebAPIPluginCLIDesktop
Categories
🧠 Agent Memory & Runtimes🔌 MCP Servers & Agent Tooling
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
Shared memory for AI agents via MCP
Streamable HTTP MCP endpoint at api.pumadb.ai/mcp
Email sign-in with OAuth handled by pumaDB, no key pasted into the client
OAuth discovery and dynamic client registration
REST API under /v1/{table} with puma_live_ bearer keys
Schema-less JSON tables created on first write
Rows stamped with id, created_at, and updated_at
Automatic version history, last 10 versions per row, retained 30 days
Row-level restore from archived versions
Batch operations and upsert endpoints
Update-row endpoint with filtered updates
Viewer and download links for sharing results
Named API keys per app or environment
Per-key rate limits (30 writes, 60 reads per minute)
Magic-link authentication for API key creation
Scrape a single page into markdown, JSON, HTML, raw, or plain text
Crawl entire sites with each page streamed as one JSONL line in order the moment it finishes
Web search endpoint returns SERP results plus the scraped pages behind them in one call
Custom browser renders like a user: scripts run, lazy images load, infinite scroll reaches the end
Unblocker loads protected pages through a real browser engine, geo checks included, returning a 200
Browser Cloud runs full sessions with anti-detection and rotating residential/ISP exits
Send AI commands (Act, Extract, Observe) over the Browser API WebSocket
Send a prompt on a scrape or crawl request and get named fields back as JSON
Two-phase AI extraction: a fast model for most pages, a stronger model for complex layouts
extraction_schema parameter makes AI output conform to a JSON schema on every extraction model
Provider router sends scrape and crawl requests to outside providers on your own keys
Data connectors pipe crawl results into S3, GCS, Google Sheets, Azure Blob, or Supabase
Proxy network with 215M+ residential and ISP exits in 199 countries, rotated per request
MCP server at mcp.spider.cloud for Claude Code, Codex, Cursor, and Claude Desktop
1,000+ ready-made scraper examples across 32 categories, each with working code
Integrations
ChatGPT
Claude
Codex
OpenClaw
LangChain
LlamaIndex
CrewAI
FlowiseAI
Langflow
Dify
Agno
MCP
Claude Code
Cursor
Claude Desktop
Amazon S3
Google Cloud Storage
Google Sheets

What real users say: pumaDB vs Spider Cloud

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

pumaDB

7 mentions across 1 sources · 75% positive (averaged across 1 source)

Product Hunt

What users praise

  • • Dead simple setup: no database project or schema design needed.
  • • MCP and REST APIs make integration with ChatGPT and Claude trivial.
  • • Automatic version history for all updates and deletes.
  • • Consolidated 'remember' MCP tool with safety metadata.

What frustrates them

  • • No automatic memory capture—agents must explicitly save state.
  • • Memory inspection and correction tools are unaddressed by builder.
  • • Limited community presence outside Product Hunt launch thread.
  • • Free tier table/row limits may not suit serious production workloads.

Researched Jul 2, 2026

Spider Cloud

No verifiable community signal. We scanned public discussion on Oct 7, 2026 and found posts matching the name “Spider Cloud”, but could not establish that they are about this product rather than something else sharing its name. Rather than publish a score built on the wrong subject, we publish none.

Who should pick which

  • Solo founder building an AI research agent
    Pick: Spider Cloud

    Needs real-time web data for answering queries; Spider Cloud’s scraping API and browser commands fetch fresh content efficiently.

  • Developer adding persistent memory to a Claude agent
    Pick: pumaDB

    pumaDB’s MCP integration with Claude enables storing notes, handoffs, and state across sessions without setting up a database.

  • Team building a RAG pipeline with LangChain
    Pick: Spider Cloud

    Spider Cloud integrates natively with LangChain and provides structured output suitable for indexing into a vector store.

  • Startup prototyping an agent handoff system
    Pick: pumaDB

    pumaDB’s lightweight JSON storage with version history is ideal for passing context between agents without overhead.

  • Enterprise needing to scrape 10M pages/month
    Pick: Spider Cloud

    Spider Cloud’s Rust engine and bulk data connectors handle high volume at low cost; pumaDB’s 1K row limit would be insufficient.

Frequently Asked Questions

pumaDB vs Spider Cloud: which should you choose?

Choose Spider Cloud if your AI agent needs fresh, structured web data at scale with low cost and rich integrations. Choose pumaDB if your priority is simple, schema-less persistent memory for agent state, handoffs, and notes without database overhead. They solve different problems: one feeds data in, the other stores it.

Can Spider Cloud and pumaDB be used together?

Yes. Spider Cloud fetches web data, and pumaDB stores structured results or agent state.

Does Spider Cloud support real-time crawling?

Yes, via its API and Browser AI WebSocket commands (Act, Extract, Observe).

Does pumaDB support authentication for MCP clients?

Yes, via email OAuth for MCP and bearer tokens (puma_live_* keys) for REST API.

What is the maximum storage in pumaDB?

Free tier: 20 tables, 1,000 rows per table, with a total database limit of 25MB.

Does Spider Cloud offer a self-hosted option?

Its open-source core is available on GitHub, so partial self-hosting is possible.

Can pumaDB handle batch updates?

Yes, it provides batch operations and upsert endpoints.

How does Spider Cloud handle anti-bot measures?

It includes an Unblocker with rotating proxies and automatic retries, plus a Silk AI model for captcha solving.

Is pumaDB suitable for high-traffic production?

Not recommended; it is designed for lightweight agent memory, not high concurrency.

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Explore each tool further

pumaDB
View pumaDB reviewpumaDB alternatives
Spider Cloud
View Spider Cloud reviewSpider Cloud alternatives

Browse these categories

Best AI Agent Memory & Runtimes toolsBest AI Web Scraping & Search APIs toolsBest AI MCP Servers & Agent Tooling toolsBest AI Browser & Computer-Use Agents tools
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Last reviewed: July 2, 2026