Shodh Memory 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

DimensionShodh MemorySpider Cloud
CategoryAI agent memory (local, offline)Web crawling & scraping API
Core TechnologyHebbian learning + knowledge graphRust engine + AI extraction
Integration37 MCP tools, Claude, LangChain, ROS2LangChain, LlamaIndex, CrewAI, S3, GCS
Key FeatureZero LLM calls, microsecond lookupsSearch endpoint, Browser AI commands, 99.9% uptime
Best ForOffline agents, edge AI, roboticsRAG pipelines, real-time web data

Choose Shodh Memory if you need deterministic, local-first memory for autonomous agents with no LLM dependency and privacy—perfect for robotics and edge. Choose Spider Cloud if you need fast, reliable web scraping and crawling to feed real-time data into AI agents or RAG pipelines. They solve entirely different problems; the right pick depends on whether your bottleneck is memory persistence or data acquisition.

Shodh Memory
Shodh Memory

Zero-LLM persistent agent memory — Hebbian learning and decay curves in a single 30MB Rust binary.

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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
Custom
$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
WebMobileDesktopAPIPluginCLI
WebAPIPluginCLIDesktop
Categories
🧠 Agent Memory & Runtimes
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
Zero LLM calls in the memory loop — no API round-trip on store or recall
Hebbian learning with Long-Term Potentiation for co-accessed memories
Hybrid decay: exponential for the first three days, then power-law heavy tail
Vamana vector index + Hebbian knowledge graph + temporal decay index
Hybrid ranking across vector, graph, and time
Causal retrieval through backward graph walks
Blind spot, shallow knowledge, orphaned cluster, and stale zone detection
Spreading activation, interference detection, and memory replay during consolidation
Sub-microsecond graph lookups (<1μs) and 34–58ms semantic search
Cowan's three-tier memory: sensory buffer (~7 items), working memory (~4 chunks), long-term
Single ~30MB Rust binary — no Docker, no external dependencies
MCP integration (37–45 tools) plus REST API with health endpoint, auth, rate limiting, CORS
Client libraries for npm (@shodh/memory-mcp), PyPI (shodh-memory), and crates.io
Runs offline on Raspberry Pi Zero, Jetson, industrial PCs, air-gapped systems
Local-only operation — data never leaves the machine, no API keys
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
Claude Desktop
Cursor
Windsurf
VS Code (Continue extension)
LangChain
LlamaIndex
OpenAI SDK
ROS2
Zenoh
Docker
CrewAI
FlowiseAI
Langflow
Dify
Agno
MCP
Codex
Amazon S3
Google Cloud Storage
Google Sheets

What real users say: Shodh Memory 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.

Shodh Memory

5 mentions across 2 sources · 75% positive (averaged across 2 sources)

Hacker News, GitHub

What users praise

  • • Zero LLM calls for memory operations—fast and cost-free.
  • • Fully offline; data never leaves the machine.
  • • Single ~30MB Rust binary, no Docker or dependencies.
  • • Hebbian learning and decay curves mimic biological memory.

What frustrates them

  • • Very early stage—only 227 GitHub stars and 9 issues.
  • • Sparse documentation for advanced features.
  • • No cloud sync or collaborative shared memory.
  • • Limited community examples and third-party tutorials.

Researched Jul 3, 2026

Spider Cloud

No verifiable community signal. We scanned public discussion on Oct 14, 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

  • Robotics engineer building an autonomous drone
    Pick: Shodh Memory

    Shodh runs offline on Raspberry Pi/Jetson with no LLM calls, providing deterministic persistent memory for navigation decisions via ROS2/Zenoh.

  • AI agent developer needing real-time web data for RAG
    Pick: Spider Cloud

    Spider Cloud's search endpoint and structured output (markdown) feed fresh content into LlamaIndex or LangChain pipelines with low cost per page.

  • Privacy-conscious developer for a medical chatbot
    Pick: Shodh Memory

    Shodh operates entirely locally with no data leaving the machine, meeting strict compliance requirements without LLM involvement in memory.

  • Data scientist scraping 10,000 product pages for training
    Pick: Spider Cloud

    Spider Cloud's Rust engine provides fast, reliable scraping with 99.9% uptime, and the scraper catalog (1,000+ examples) reduces development time.

  • Edge AI researcher experimenting with cognitive architectures
    Pick: Shodh Memory

    Shodh's Hebbian learning and causal retrieval align with cognitive science models (ACT-R); its open-source code allows full customization.

Frequently Asked Questions

Shodh Memory vs Spider Cloud: which should you choose?

Choose Shodh Memory if you need deterministic, local-first memory for autonomous agents with no LLM dependency and privacy—perfect for robotics and edge. Choose Spider Cloud if you need fast, reliable web scraping and crawling to feed real-time data into AI agents or RAG pipelines. They solve entirely different problems; the right pick depends on whether your bottleneck is memory persistence or data acquisition.

Can Shodh Memory work together with Spider Cloud?

Yes. Spider Cloud can fetch web data, which is then stored in Shodh's knowledge graph for persistent, causal memory—no LLM needed for the memory loop.

Does Shodh Memory require an internet connection?

No. Shodh is designed for local-only operation and works fully offline, even on air-gapped systems.

Does Spider Cloud offer a free trial?

Yes, Spider Cloud has a free tier with limited credits to test the API before committing to paid usage.

How fast are Shodh's lookups?

Sub-microsecond for graph lookups and 34–58ms for semantic search, thanks to the Rust binary and optimized hybrid ranking.

What is Spider Cloud's success rate?

Spider Cloud advertises 99.9% success rate with automatic retries and rotating proxies.

Can I self-host Spider Cloud?

Yes, Spider Cloud has an open-source core on GitHub that can be self-hosted, though the cloud version offers additional features like AI Studio and unblocker.

Does Shodh Memory support team sharing?

Not natively. Shodh is local-first; multi-user sync would need custom implementation via its REST API.

Which integrations does Spider Cloud have for AI agents?

Spider Cloud integrates with LangChain, LlamaIndex, CrewAI, AutoGen, Agno, Dify, and more, plus data connectors to cloud storage.

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Last reviewed: July 3, 2026