easy-agent MCP Server
ConardLi/easy-agent
[](https://agentrank-ai.com/tool/ConardLi--easy-agent/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Production-ready open source terminal coding agent with readable, layered code: permission rules, OS sandboxing, MCP, skills, sub-agents, and Anthropic, OpenAI-compatible, Gemini, or local models.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
ConardLi/easy-agent is a TypeScript tool licensed under MIT. Production-ready open source terminal coding agent with readable, layered code: permission rules, OS sandboxing, MCP, skills, sub-agents, and Anthropic, OpenAI-compatible, Gemini, or local models. Topics: agent, ai-agent, anthropic, cli, coding-agent, developer-tools, gemini, llm, mcp, openai, sandbox, terminal, typescript.
Ranked #3818 out of 24846 indexed tools.
Has 1,010 GitHub stars.
Ecosystem
Score Breakdown
1,010 stars → well-known project
Last commit 8d ago → recently updated
36/49 issues closed → decent issue management
1 contributor → solo project
No dependents → no downstream usage
3 weekly installs → early adoption
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
How to Improve
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From the README
# Easy Agent A terminal coding agent that reads your code, edits files, and runs commands under permission rules you control. Easy Agent (`eagent`) runs in your terminal next to your repository. Describe a task and it plans the work, reads and changes files, runs tests or shell commands, and reports back. Every action that can change your machine goes through permission rules, workspace trust, and an optional OS-level sandbox. It works with Anthropic, OpenAI-compatible, Gemini, and local models. The code is written to be read as well as run. Model communication, the agentic loop, tools, permissions, context management, and each extension system live in separate layers. The documents linked below explain how the security-relevant parts behave and why, and the [learning path](./docs/learning-path.md) walks through the layers in order with code snapshots, which helps if you want to build or customize an agent of your own. > 中文文档：[README.zh-CN.md](./README.zh-CN.md) ## What you can usRead full README on GitHub →
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