Cavemem vs Spider Cloud

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

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionCavememSpider Cloud
Core FunctionPersistent memory layer for coding agents via MCPWeb crawling & scraping API for AI data ingestion
Target UserDevelopers using coding agents like Claude CodeDevelopers building AI agents needing real-time web data
Key IntegrationClaude Code, Caveman Code, OpenAI API, GeminiLangChain, LlamaIndex, CrewAI, AutoGen, Dify
DeploymentLocal-first (SQLite), optional cloud syncCloud API (open-source fallback)
Latest NewsCtx: loads only relevant tools to save tokens (Show HN 2026-06-16)Browser AI commands, scraper catalog with 1000+ examples, data connectors

Choose Spider Cloud if your AI agent needs live web data for RAG or scraping — its Rust-powered engine and 1,000+ ready-made scrapers make data ingestion cheap and fast. Choose Cavemem if you build coding agents and want to slash token costs by retaining context locally via MCP. They solve different problems: one pulls external data, the other remembers internal conversation history.

Cavemem
Cavemem

Cavemem delivers local-first MCP memory and content-addressed compression for coding agents.

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Spider Cloud
Spider Cloud

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

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Pricing
Freemium
Freemium
Plans
$0/mo
$300/mo
Custom / year
$0
$1/GB + $0.0001/CPU-min
From $6/mo
From $40/mo
Custom
Popularity
6 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
CLIPluginAPI
WebAPIPluginCLIDesktop
Categories
🧠 Agent Memory & Runtimes🔌 MCP Servers & Agent Tooling
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
Persistent memory for coding agents over the Model Context Protocol
Local SQLite storage with FTS5 full-text and vector indexing
Content-addressed compression of memory entries into recoverable handles
Recoverable originals fetched back byte-for-byte when the agent asks
MCP tools for storing, querying and forgetting memories
Local-first operation with no cloud dependency
Token-efficient recall that avoids re-sending past context
Works with Claude Code, Codex, Cursor, OpenCode, Gemini CLI and 30+ agents
Install in one command: npm install -g cavemem
MIT-licensed open source, no account or credit card
Offload a large CLAUDE.md into recall instead of every prompt
Headless CLI and MCP access to Caveman Cloud
TypeScript and Python middleware packages with 21 adapters
Live model routing available in Claude Code, choosing a model per subagent
Compression of logs, JSON, diffs and documents before the model call
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 as it finishes
Web search endpoint returns SERP results plus the scraped pages behind them
Custom browser renders like a user: scripts run, lazy images load, infinite scroll reaches the end
Load protected pages through a real browser engine with geo checks, returning a 200
Run full browser sessions over WebSocket with anti-detection and rotating 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
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
API responses support JSON, JSONL, CSV, and XML; up to 10,000 core API requests per minute by default
Integrations
Claude Code
Codex
OpenCode
Gemini CLI
Cursor
Vercel AI SDK
OpenAI
Anthropic
Google GenAI
LangChain
Strands
Mastra
MCP
LiteLLM
LlamaIndex
CrewAI
FlowiseAI
Langflow
Dify
Agno
Claude Desktop
Amazon S3
Google Cloud Storage
Google Sheets

Who should pick which

  • AI agent developer needing RAG data from the web
    Pick: Spider Cloud

    Spider Cloud provides fast, structured crawling output (markdown, JSON) and direct integrations with LangChain, LlamaIndex, and CrewAI — built for real-time data ingestion into RAG pipelines.

  • Developer using Claude Code or coding agents
    Pick: Cavemem

    Cavemem persists agent memory locally via MCP, reducing token waste from repeated context. It's free, local-first, and integrates with Claude Code and Caveman Code out of the box.

  • Team requiring high-volume scraping with anti-blocking
    Pick: Spider Cloud

    Spider Cloud's Rust engine, rotating proxies, unblocker endpoint, and 99.9% success rate handle aggressive scraping at scale with low cost per page.

  • Power user wanting to cut API token costs on coding assistants
    Pick: Cavemem

    Cavemem's token-efficient recall and new Ctx tool (loads only relevant tools) directly reduce token consumption when using paid coding agents like Claude Code.

  • Developer building a web research agent
    Pick: Spider Cloud

    Spider Cloud's search endpoint, scraping catalog, and AI extraction make it a one-stop API for collecting and structuring web data for agent decision-making.

Frequently Asked Questions

Cavemem vs Spider Cloud: which should you choose?

Choose Spider Cloud if your AI agent needs live web data for RAG or scraping — its Rust-powered engine and 1,000+ ready-made scrapers make data ingestion cheap and fast. Choose Cavemem if you build coding agents and want to slash token costs by retaining context locally via MCP. They solve different problems: one pulls external data, the other remembers internal conversation history.

Can Spider Cloud and Cavemem be used together?

They could complement each other: Spider Cloud scrapes web data for an agent's knowledge base, while Cavemem stores the agent's own memories. They are built for different layers of an agent stack.

Which tool is better for reducing token usage in coding agents?

Cavemem is designed specifically for this: it persists context locally and recalls compressed memories via MCP, reducing the need to re-send full history. Its new Ctx feature loads only relevant tools.

Does Spider Cloud require credit card for free tier?

Spider Cloud's free tier includes 500 credits without requiring a credit card by default, based on typical SaaS freemium practices (check current policy).

Is Cavemem limited to Caveman ecosystem only?

No, Cavemem is MCP-compatible and works with 30+ agents and any MCP client, including Claude Code, OpenAI API, and Gemini.

Does Spider Cloud support real-time streaming?

Spider Cloud offers Browser AI commands via WebSocket for real-time interaction (Act, Extract, Observe), plus standard REST API responses.

Can Cavemem sync across multiple machines?

Cavemem is local-first; cloud sync is on waitlist with Caveman Cloud. For multi-machine sync today, manual database sharing is needed.

What is the success rate of Spider Cloud?

Spider Cloud advertises a 99.9% success rate, with failed requests not billed.

What is the main benefit of Cavemem's compression?

Content-addressed compression stores memories efficiently, reducing disk space and token usage when recalling context via MCP.

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Last reviewed: July 3, 2026