Toolspool.ai

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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

exa.ai
✓ verifiedFreemium

Web search API and AI web researcher for AI applications; category-defining infrastructure.

👁 761K/mo1.7K
👁 21K/mo

Thin 'Lingbot-map' agent listing on github.com with zero traffic; too thin to tell.

5.2K
Pricing
Free: $0 (20,000 requests/month)
Search: $7 per 1k requests (up to 10 results)
Contents: $1 per 1k pages
Deep Search: $12-15 per 1k requests
Monitors: $15 per 1k requests

Free trial available

DEVELOPER: FREE
STARTER: $119 / month
GROWTH: $599 / month
ENTERPRISE: Starting at $1,800 / month

No public pricing

Core features
  • Web Search API
  • Web Crawling
  • LLM Answers
  • Websets for data enrichment
  • Developer-first platform for AI-powered integrations
  • Secure, isolated sandboxes for running JavaScript/Python code
  • Automatic management of npm/PyPI dependencies
  • Built-in platform plumbing: secrets, webhooks, scheduling, logs, and audit
  • Yep Agent (prompt → runnable processes)
  • MCP Server/Tools (convert code into AI agent tools)
  • Serverless runtime (YepCode Run) and SDK access
  • Fast tensor operations
  • Differentiable tensors for gradient-based optimization
  • Network connectivity
  • Integration with Bun and Flashlight
  • Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
Use cases
  • Summarize news on any topic
  • Collect information about a company across news, socials, and databases
  • Search for relevant sources and synthesize into a reliable report
  • Ask questions and get answers with RAG
  • Find and evaluate potential candidates for recruiting
  • Building complex API integrations that require custom code and logic beyond what no-code tools offer.
  • Safely running AI-generated scripts in isolated environments with secrets management.
  • Automating workflows that require large datasets, loops, branching, or custom dependencies.
  • Connecting AI agents to external databases, APIs, and services using MCP tools.
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
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