Hebbrix 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

DimensionHebbrixSpider Cloud
Core FunctionOutcome-weighted persistent memory for AI agentsWeb crawling & scraping API for AI agents
Best ForProduction agents needing cross-session memoryRAG pipelines needing real-time web data
Engine5-layer hybrid search + knowledge graphRust-based fast crawling
Unique FeatureSelf-improving retrieval with reinforcement learningBrowser AI commands (Act, Extract, Observe) via WebSocket
IntegrationOpenAI, LangChain, LangGraph, MCP server, CrewAI, Claude, Cline, Neo4jLangChain, LlamaIndex, CrewAI, FlowiseAI, AutoGen, Agno, Dify, cloud storage

Spider Cloud and Hebbrix solve different problems. If your AI agent needs to fetch fresh web data for RAG or scraping, Spider Cloud’s Rust engine and Browser AI commands are unmatched. If you need persistent, self-improving memory for agents (customer support, voice, etc.), Hebbrix’s outcome-weighted recall and knowledge graph are a game-changer. Choose based on your primary need: external data or internal memory.

Try HebbrixTry Spider Cloud
Hebbrix
Hebbrix

Hebbrix is persistent agent memory that ranks recall by reported outcomes, not text similarity.

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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
$19/mo
$99/mo
$399/mo
Pay as you go
$1/GB + $0.0001/CPU-min
From $6/mo
From $40/mo
Custom
Popularity
2 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
APIWeb
WebAPIPluginCLIDesktop
Categories
🧠 Agent Memory & Runtimes
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
Outcome-weighted recall ranks memory by reported success or failure, not text similarity
Five retrieval layers: adaptive semantic, lexical, knowledge graph, temporal and feedback signals
One-line OpenAI drop-in: change base_url to api.hebbrix.com/v1
Chat completions endpoint with automatic memory retrieval and context injection
Outcome Memory API with decision receipts, delayed outcomes and posterior uncertainty
Knowledge graph with entity extraction, relationship mapping and fact-replacement tracking
3-tier memory with automatic promotion across short, mid and long-term stores
Memory decay driven by usage, recency, importance, corrections and reported outcomes
Missing feedback treated as unknown rather than failure
Collections for organizing memories in multi-tenant applications
MCP server 0.5.14 with 33 live tools for MCP-compatible agents
Coding agent MCP integration for Claude, Cline and other MCP clients
Explicit /memories/process index waits (wait_for_index, bounded index_wait_seconds)
Opt-in selection methods with experimental outcome-policy-v3 ranking
Memory-off chat that preserves caller instructions without hidden profile injection
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
OpenAI
Anthropic
LangChain
LangGraph
CrewAI
MCP server
Dify
LlamaIndex
FlowiseAI
Langflow
Agno
MCP
Claude Code
Codex
Cursor
Claude Desktop
Amazon S3
Google Cloud Storage
Google Sheets

Who should pick which

  • AI Agent Developer (RAG)
    Pick: Spider Cloud

    Spider Cloud provides fast, structured web data extraction with its Rust engine and Browser AI commands, ideal for RAG pipelines needing up-to-date content.

  • Customer Support Bot Builder
    Pick: Hebbrix

    Hebbrix’s outcome-weighted memory ensures the bot remembers user preferences and past interactions across sessions, improving support quality.

  • Data Scientist (Web Scraping)
    Pick: Spider Cloud

    With 1,000+ scraper examples, data connectors, and low cost per page, Spider Cloud efficiently collects large datasets.

  • Voice Agent Developer
    Pick: Hebbrix

    Hebbrix’s memory decay and self-improving retrieval align with voice agents that need to recall user preferences over time without storing irrelevant noise.

  • LangChain User
    Neither is a clear fit

    Both integrate with LangChain: Spider Cloud for data retrieval, Hebbrix for memory. A combined solution is powerful for advanced agents.

Frequently Asked Questions

Hebbrix vs Spider Cloud: which should you choose?

Spider Cloud and Hebbrix solve different problems. If your AI agent needs to fetch fresh web data for RAG or scraping, Spider Cloud’s Rust engine and Browser AI commands are unmatched. If you need persistent, self-improving memory for agents (customer support, voice, etc.), Hebbrix’s outcome-weighted recall and knowledge graph are a game-changer. Choose based on your primary need: external data or internal memory.

Can I use Spider Cloud and Hebbrix together?

Yes, they complement each other. Spider Cloud fetches web data, Hebbrix stores agent memory, both integrate with LangChain and CrewAI.

Which is better for RAG?

Spider Cloud is better for fetching external data; Hebbrix is better for storing retrieved context as memory. Use both for optimal RAG.

Does Hebbrix support self-hosting?

Enterprise plans may include on-premise options, but free/paid tiers are cloud-based. Contact sales for details.

Is Spider Cloud open-source?

Its core is open-source on GitHub, but the cloud version with premium features like AI Studio and Browser AI is proprietary.

What is Hebbrix’s pricing after free tier?

Paid tiers start at $20/month for 10,000 credits. Custom enterprise pricing is available.

Can Spider Cloud handle JavaScript-heavy sites?

Yes, its Browser Cloud uses stealth anti-detection and can execute JavaScript for dynamic content.

Does Hebbrix work with any LLM?

Yes, via its OpenAI-compatible endpoint, it works with any model that supports that API format.

Which tool has better integrations?

Spider Cloud has more data connectors; Hebbrix integrates with more agent frameworks and MCP. Depends on your stack.

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Explore each tool further

Hebbrix
View Hebbrix reviewHebbrix 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 Browser & Computer-Use Agents tools
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Last reviewed: July 3, 2026