Erold is an AI-native project management platform built specifically for developers and AI agents to collaborate. It features MCP server integration, REST API, CLI tool, and a knowledge base that gives AI persistent memory across sessions.

How does Erold integrate with Claude Code?

Erold provides a native MCP (Model Context Protocol) server with 18 tools that Claude Code can use directly. This allows Claude to create tasks, update progress, access project knowledge, and manage your projects without any copy-paste.

Yes! Erold offers a free tier with 1 project and unlimited tasks. Pro is $5/month with pay-as-you-go pricing for extra resources. Only pay for what you use beyond included allocations.

What AI tools does Erold support?

Erold works with any AI tool that supports MCP or REST APIs, including Claude Code, Claude Desktop, Cursor, Windsurf, GitHub Copilot, and custom AI agents. The API-first design ensures compatibility with current and future AI tools.

What is MCP (Model Context Protocol)?

MCP (Model Context Protocol) is a standard protocol that allows AI assistants to interact with external tools and services. Erold's MCP server provides 18 tools for task management, knowledge base access, and project operations that AI assistants can use directly.

How is Erold different from Jira, Linear, or Asana?

Erold is built API-first for AI agents, not humans-first with APIs added later. Traditional tools require copy-paste to share context with AI. Erold lets AI assistants read tasks, update progress, and access project knowledge directly through MCP, API, or CLI.

What is the Knowledge Base feature?

The Knowledge Base is persistent memory for AI assistants. Store project context, coding standards, architecture decisions, and any information AI should remember across sessions. AI can read and write knowledge entries, making it smarter about your specific project over time.

Does Erold have a CLI tool?

Yes! The Yet CLI (npm install -g @erold/cli) provides full task management from your terminal. Create tasks, list projects, mark items done, and integrate with git workflows. Perfect for developers who prefer command-line tools.

When should I use Caching Strategies?

Configuring HTTP caching. Setting up CDN. Optimizing API response times. Implementing offline support

When should I NOT use Caching Strategies?

Real-time data requirements. User-specific content without cache keys

Performance optimization recommended

Caching Strategies

Browser caching, CDN configuration, HTTP cache headers, service workers, and API caching strategies for web applications.

Difficulty: intermediate
Read time: 1 min read
Version: v1.0.0
Confidence: established
Last updated: Updated Jan 8, 2026

Edit on GitHub Report Issue

Quick Reference

Use Cache-Control headers: immutable for hashed assets, max-age + stale-while-revalidate for dynamic. CDN: cache static assets at edge. Browser: leverage ETags and Last-Modified. API: use Redis/memory cache with TTL. Service workers for offline-first. Invalidate on deploy with cache busting.

Use When

Configuring HTTP caching
Setting up CDN
Optimizing API response times
Implementing offline support

Skip When

Real-time data requirements
User-specific content without cache keys

Caching Strategies

Browser caching, CDN configuration, HTTP cache headers, service workers, and API caching strategies for web applications.

Discussion

Caching Strategies recommended Performance Optimization recommended Bundle Size Optimization recommended Core Web Vitals Optimization recommended

Caching Strategies

Quick Reference

Use When

Skip When

Caching Strategies

Discussion

Strictly Necessary

Analytics

Functional