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 State Machine Patterns?

Multi-step forms. Complex UI flows. Order/payment workflows. Authentication flows

When should I NOT use State Machine Patterns?

Simple boolean toggles. Basic CRUD operations. Server-only logic

Design Patterns state-machines recommended

State Machine Patterns

Model complex workflows with state machines using XState and explicit state transitions.

Difficulty: advanced
Read time: 1 min read
Version: v1.0.0
Confidence: established
Last updated: Updated Jan 9, 2026

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Quick Reference

State Machines: Use XState for complex UI flows. Define explicit states and transitions. Guards validate transitions. Actions trigger side effects. Use invoke for async operations. Impossible states become impossible. Visualize with Stately.ai.

Use When

Multi-step forms
Complex UI flows
Order/payment workflows
Authentication flows

Skip When

Simple boolean toggles
Basic CRUD operations
Server-only logic

State Machine Patterns

Model complex workflows with state machines using XState and explicit state transitions.

Discussion

Factory Pattern recommended Observer Pattern & Pub/Sub recommended Result/Either Pattern recommended Strategy Pattern recommended

State Machine Patterns

Quick Reference

Use When

Skip When

State Machine Patterns

Discussion

Strictly Necessary

Analytics

Functional