Projectmem 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

DimensionProjectmemSpider Cloud
Core FunctionLocal memory layer for AI coding agentsWeb crawling, scraping, search API for AI agents
Primary Use CasePersistent context for coding agents (Claude, Cursor)RAG pipelines, real-time web data for LLMs
Data Storage100% local, no cloudCloud-based API, optional connectors to S3/GCS
Key FeatureMCP server, records issues & decisions across sessionsRust engine, 99.9% uptime, AI Studio with natural language crawling
Target AudienceDevs using AI coding agents wanting memoryDevs building AI agents needing web data

Spider Cloud and Projectmem serve entirely different needs. Spider Cloud is a web scraping API optimized for AI agents needing fresh external data—ideal for RAG and LLM context. Projectmem is a local memory layer that gives coding agents persistent project context across sessions. Choose Spider Cloud if your agent needs to fetch and structure live web content; choose Projectmem if you want your coding assistant to remember past fixes and architectural decisions without leaving your machine.

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Projectmem
Projectmem

Local-first coding agent memory that records issues, failed attempts and fixes inside your repo and feeds them back to Claude Code, Cursor or Codex at session

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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
Free
Freemium
Plans
$0
$1/GB + $0.0001/CPU-min
From $6/mo
From $40/mo
Custom
Popularity
5 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
CLIPlugin
WebAPIPluginCLIDesktop
Categories
🧠 Agent Memory & Runtimes🔌 MCP Servers & Agent Tooling
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
Append-only event log stored in a .projectmem/ directory inside your repository
Git hooks auto-classify commits: reverts become failed attempts, fix commits become fix events
pjm precheck warns about failed approaches on staged files before a commit lands
pjm wrap injects a token-budgeted memory block into an agent session
Native MCP server exposing 17 tools across all registered projects
One MCP server configuration serves every repository, no --root and no cwd
pjm doctor finds unregistered projects with existing memory and flags misconfigured clients
Cross-project memory at ~/.projectmem/global/ carries library gotchas between repositories
pjm score grades memory ROI A+ to F with debugging hours, tokens and dollars saved
Works with Claude Code, Cursor, Codex, Antigravity and other MCP agents
Universal Mode: distilled markdown files for agents without MCP
Interactive local dashboard with 6 tabs run via pjm dashboard --serve
Stale-entry detection with git verification: flags staleness, never deletes history
CLAUDE.md export for agents working without MCP
25 CLI commands, installed with pip install -U projectmem
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
Cursor
Codex
Antigravity
Gemini
Windsurf
Goose
Grok
DeepSeek
GLM
Qwen
Ollama
Aider
LangChain
LlamaIndex
CrewAI
FlowiseAI
Langflow
Dify
Agno
MCP
Claude Desktop
Amazon S3
Google Cloud Storage
Google Sheets

Who should pick which

  • Developer building an AI agent that needs to answer questions about current web pages
    Pick: Spider Cloud

    Spider Cloud provides real-time crawling and structured extraction (markdown, HTML, JSON) perfect for RAG pipelines. Its AI extraction and Browser AI commands can pull data from dynamic sites.

  • Coding agent user who wants the agent to remember past fixes across sessions
    Pick: Projectmem

    Projectmem records issues and attempted solutions in a local MCP server, so agents like Claude Desktop and Cursor can recall context without starting from scratch.

  • Privacy-conscious developer wanting a memory layer for coding agents
    Pick: Projectmem

    Projectmem stores everything locally with no telemetry or cloud dependency, ensuring full control over sensitive project data.

  • Team scraping thousands of pages for LLM training data
    Pick: Spider Cloud

    Spider Cloud's Rust engine and high success rate (99.9%) make it suitable for high-volume scraping at low cost. Data connectors allow piping results directly to cloud storage.

Frequently Asked Questions

Projectmem vs Spider Cloud: which should you choose?

Spider Cloud and Projectmem serve entirely different needs. Spider Cloud is a web scraping API optimized for AI agents needing fresh external data—ideal for RAG and LLM context. Projectmem is a local memory layer that gives coding agents persistent project context across sessions. Choose Spider Cloud if your agent needs to fetch and structure live web content; choose Projectmem if you want your coding assistant to remember past fixes and architectural decisions without leaving your machine.

Can Spider Cloud be used for real-time data retrieval?

Yes, its search endpoint and crawling API provide up-to-date content. Recent updates include Browser AI commands via WebSocket for live interactions.

Can Projectmem work with non-MCP agents?

Currently, it targets MCP-compatible tools like Claude Desktop and Cursor. Non-MCP agents would require custom integration.

Does Spider Cloud offer an open-source version?

Yes, the core is available on GitHub for self-hosting, though the cloud API offers additional features and reliability.

Is Projectmem suitable for multi-device use?

No, it is local-first and does not sync across devices. Each machine has its own memory store.

What AI models does Spider Cloud use for extraction?

It uses its own Silk custom AI model for extraction and captcha solving. Recent news (2026-02-10) mentions a two-phase fallback with fast and capable models.

How does Projectmem store data?

It uses lightweight file-based storage locally on your machine. No cloud database is involved.

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Explore each tool further

Projectmem
View Projectmem reviewProjectmem 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 3, 2026