Runx
AI Skill Hub 强烈推荐：Runx 是一款优质的MCP工具。AI 综合评分 8.0 分，在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案，这是一个值得深入了解的选择。
📚 深度解析
通过安装 Runx，你的 AI 助手将获得额外的工具调用能力，可以用自然语言直接操控该工具的功能，无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置，永久增强"——配置完成后，每次与 AI 对话时都可以无缝调用这些工具。
在技术实现上，MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信，工具的功能以"工具列表"的形式暴露给 AI 模型，AI 可以按需调用。Runx 提供了结构化的工具调用接口，使 AI 模型能够精确地理解和使用每个功能点，显著降低 AI 在工具使用上的错误率。
与传统的 API 集成相比，MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON，即可让 AI 获得全新能力。AI Skill Hub 将 Runx 评为 AI 评分 8.0 分，属于同类工具中的优质选择。
📋 工具概览
Runx 是一款遵循 MCP（Model Context Protocol）标准协议的 AI 工具扩展。通过 MCP 协议，它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务，实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用，都可以通过自然语言在 AI 对话中直接触发，极大提升生产效率。
📖 中文文档
Runx 是一款遵循 MCP（Model Context Protocol）标准协议的 AI 工具扩展。通过 MCP 协议，它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务，实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用，都可以通过自然语言在 AI 对话中直接触发，极大提升生产效率。
- 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
- 提供结构化工具调用接口，显著降低 AI 集成复杂度
- 支持 Claude Desktop 和 Claude Code 无缝接入，开箱即用
- 可与其他 MCP 工具组合叠加，构建完整 AI 工作站
- 轻量无侵入设计，不影响现有系统架构
- 在 Claude Desktop 对话中直接调用本地工具，实现 AI 与系统的深度联动
- 通过自然语言驱动复杂的多步骤自动化任务，代替繁琐手动操作
- 将多个 MCP 工具组合使用，构建个人专属 AI 工作站
# 方式一：通过 Claude Code CLI 一键安装
claude skill install https://github.com/runxhq/runx
# 方式二：手动配置 claude_desktop_config.json
{
"mcpServers": {
"runx": {
"command": "npx",
"args": ["-y", "runx"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
- 确认已安装 Node.js（v18 或以上版本）
- 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
- 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
- 保存配置文件并重启 Claude 客户端
- 重启后，在对话中即可使用本工具
# 安装后在 Claude 对话中直接使用 # 示例： 用户: 请帮我用 Runx 执行以下任务... Claude: [自动调用 Runx MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入："列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"runx": {
"command": "npx",
"args": ["-y", "runx"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
简介
runx
<p align="center"><strong>The governed runtime for agent skills</strong></p>
<p align="center"> <a href="LICENSE"><img alt="License: Apache-2.0" src="https://img.shields.io/badge/license-Apache--2.0-111111?style=flat-square"></a> <a href="https://www.npmjs.com/package/@runxhq/cli"><img alt="npm @runxhq/cli" src="https://img.shields.io/npm/v/@runxhq/cli?style=flat-square&color=f97316&label=%40runxhq%2Fcli"></a> <a href="https://github.com/runxhq/runx/actions/workflows/ci.yml"><img alt="CI" src="https://github.com/runxhq/runx/actions/workflows/ci.yml/badge.svg"></a> <a href="https://runx.ai/x"><img alt="Skill catalog" src="https://img.shields.io/badge/catalog-runx.ai%2Fx-ff2e88?style=flat-square"></a> <a href="https://runx.ai/spec"><img alt="Specification" src="https://img.shields.io/badge/spec-read-7c5cff?style=flat-square"></a> </p>
<p align="center"> <a href="#quickstart">Quickstart</a> · <a href="#skills-working-together">Workflows</a> · <a href="#a-skill-carries-judgment">Write a skill</a> · <a href="#what-a-receipt-proves">Receipts</a> · <a href="#build-on-runx">Build on Runx</a> </p>
---
A skill is a URL.
A graph is what unfolds.
Authority narrows. It does not pass through.
Every act produces a receipt.A skill is expertise published as a portable SKILL.md: an operating manual that a human can understand and an agent can act from. It carries the method, the evidence to look for, the decisions to make, and the tools the work needs. Skills can call other skills, passing their results forward into a larger job.
Runx makes that work executable. A research brief can become an outreach draft. A product launch can connect release work, documentation, and customer updates. Search and product analytics can inform the next change to your site. Across those handoffs, Runx admits calls under explicit authority, delivers credentials at the tool boundary, supervises execution, and seals a verifiable record.
Your agent supplies the judgment. Runx owns the execution boundary. Use the CLI, MCP, or a language client with the agent or orchestration framework you already use. Execution, state, and receipt signing run locally; hosted registry, credential custody, and notary services are optional. The runtime is written in Rust and licensed under Apache-2.0.
description: Echo a message through a checked-in command.
Build on Runx
The CLI, MCP server, and language clients use the same Rust execution path. An application can start a skill, expose its open turns to a model, route human decisions, resume the run, and inspect its receipts.
| Surface | Entry point |
|---|---|
| CLI | runx skill <skill-ref> [runner] -i key=value --json — [reference](docs/reference.md#local-cli). |
| MCP | runx mcp <skill-ref> to expose a skill; runx mcp --run <run-id> to work an existing run. |
| TypeScript / Node.js | [@runxhq/client](packages/client/README.md), with explicit workspace and environment configuration. |
| Python | [Python SDK](packages/sdk-python/README.md). |
| Rust | [runx-sdk](crates/runx-sdk/README.md). |
| Contracts | [Schemas](schemas/) and the [public specification](https://runx.ai/spec). |
MCP exposes a turn's allowed calls as typed tools. The host owns the model conversation; Runx admits and records the calls. You can integrate a single skill or build a product around long-lived runs without introducing another execution implementation.
<details> <summary><strong>Inside the runtime: which layer owns what</strong></summary>
| Layer | Owner |
|---|---|
| Portable wire contracts | runx-contracts |
| Pure policy, authority, and state transitions | runx-core |
| Package parsing and validated package representation | runx-parser |
| Canonical receipts, hashing, signatures, and verification | runx-receipts |
| Execution, capabilities, processes, adapters, and effects | runx-runtime |
| Argument parsing and presentation | runx-cli |
| Language clients and extension protocols | packages/ |
| Operator knowledge and domain computation | skills/ and product-owned packages |
The system architecture defines these ownership boundaries. SDKs, exported agent skills, schemas, and catalog views consume the same contracts.
</details>
Quickstart
Hello World
Print the supplied message so the caller can inspect the local execution and its signed receipt.
When the work needs executable steps, typed inputs and outputs, authority,
artifacts, or harness cases, the package also carries a `run.yaml`:
runners: default: default: true inputs: message: type: string required: true steps: - id: default tool: { command: node, args: [run.mjs] } inputs: message: $input.message outputs: message: string ```
This is the execution shape of examples/hello-world. Its checked-in package also includes the command and harness case.
| Part | Responsibility |
|---|---|
SKILL.md and references | Expertise, procedure, judgment, recovery, and completion criteria. |
run.yaml | Executable runners, typed contracts, declared capabilities, authority, and harness cases. |
| Domain modules | Deterministic computation specific to the skill. |
| Runx | Provider transport, filesystem and process access, credential delivery, execution state, and receipts. |
Runx binds the manual and execution closure by digest. An acting agent receives the invoked skill's full manual; declared adjacent skills contribute bounded summaries until invoked. A graph can also supply a skill as explicit context_skills on an agent step—for example, a writing rubric. Context informs judgment; permission comes from admission.
Run the local workflow proofs
From this checkout:
```bash
Research → draft → channel package → publication handoff
runx harness skills/content-package/fixtures/composes-in-graph.yaml
Runx是一个高质量的开源MCP工具，具有良好的扩展性和可用性
- 构建多智能体协作系统的 Agent 开发者
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 云端托管：可放在 Vercel / Railway / Fly.io 等 PaaS 平台
⚡ 核心功能
- 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
- 提供结构化工具调用接口，显著降低 AI 集成复杂度
- 支持 Claude Desktop 和 Claude Code 无缝接入，开箱即用
- 可与其他 MCP 工具组合叠加，构建完整 AI 工作站
- 轻量无侵入设计，不影响现有系统架构
- 构建多智能体协作系统的 Agent 开发者
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
👥 适合人群
🎯 使用场景
- 在 Claude Desktop 对话中直接调用本地工具，实现 AI 与系统的深度联动
- 通过自然语言驱动复杂的多步骤自动化任务，代替繁琐手动操作
- 将多个 MCP 工具组合使用，构建个人专属 AI 工作站
⚖️ 优点与不足
- +MIT 协议，可免费商用
- +标准化 MCP 协议，生态互联性强
- +与 Claude 官方生态无缝对接
- +即插即用，配置简单快捷
- −依赖 Claude 客户端，非 Claude 用户无法使用
- −MCP 协议仍在持续演进，接口可能变更
- −需要一定的配置步骤
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一，可自由商用、修改、分发，仅需保留版权声明。
🔗 相关工具推荐
❓ 常见问题 FAQ
总体来看，Runx 是一款质量优秀的MCP工具，在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态，建议收藏备用，结合自身场景选择合适时机引入使用。
| 原始名称 | runx |
| 原始描述 | 开源MCP工具：the governed runtime for agent skill workflows, off the leash but on the record。⭐29 · Rust |
| Topics | agent-orchestrationagent-runtimeagent-skillsagentic-aiai-agents |
| GitHub | https://github.com/runxhq/runx |
| License | MIT |
| 语言 | Rust |
收录时间：2026-06-28 · 更新时间：2026-07-03 · License：MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。