Modelbound Mcp

io.github.ModelBound由 GitHub 账号 ModelBound 发布v0.1.2更新于 Nov 3, 2026

Local-first MCP server for agent skills. Validate, lint, diff, and convert across IDEs.

概览

AI 生成的概览

面向 agent 技能文件的本地优先 MCP 服务器:检测 IDE 布局,列出、读取、写入、检查、安全扫描、校验、转换和对比技能,可选 ModelBound 云端同步。

可以做什么
  • 检测仓库使用的 IDE 约定,并列出、读取或写入本地技能文件
  • 检查技能的 front-matter、token 数量、失效链接和 TODO,并离线扫描注入、数据外泄、密钥和破坏性命令等风险
  • 按 agentskills.io 规范校验技能,在 IDE 格式之间转换,并按默认范围限制生成新技能
  • 执行审核流程(查看状态、申请、批准、拒绝、门禁),可在 CI 中拦截未批准的技能
  • 配置 API 密钥后:拉取、推送、搜索、列出和安装市场技能,查看团队资源树并检查优化健康度
适用场景
适合在仓库中维护 agent 技能、规则或 steering 文件,并在 Cursor、Claude、Codex、Kiro、Windsurf、VS Code 或 Amazon Q 之间切换的场景,或希望在技能被使用前做检查和安全性扫描。只有团队把技能存放在 ModelBound 时,云端工具才有意义。
运行要求
通过 stdio 在本地运行,通常使用 npx modelbound-mcp 或全局安装 npm 包,因此需要 Node.js。本地工具无需账号或网络。云端同步工具需要环境变量 MODELBOUND_API_KEY,该密钥为可选项。
安装前请注意
该服务器可以写入本地技能文件;配置 API 密钥后还能把技能推送到 ModelBound 云端并安装市场技能,改动可能影响团队共享内容。API 密钥属于机密,不要放进共享配置。云端工具会把请求转发到托管的 ModelBound 端点,使用时技能内容会离开本机。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Modelbound Mcp,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

modelbound-mcp

Local-first MCP server for agent skills. Validate, lint, diff, and convert agent skill files across Cursor, Claude, Codex, Kiro, Windsurf, VS Code, and Amazon Q — no account required. Optional cloud sync with ModelBound.

[npm] [License: MIT] [ModelBound Skill Checks]

Why ModelBound?

AI tools come and go. You might use Cursor today, switch to Claude Code tomorrow, and try Kiro next week — but your skills, rules, and context shouldn't be locked into any one of them. ModelBound gives you a single place to store and manage your agent skills, so you can move between tools freely without rebuilding your setup each time. Write a skill once, sync it everywhere, and get more value out of every AI subscription you're already paying for.

What it does

modelbound-mcp is a small Model Context Protocol server you run locally over stdio. It exposes tools to your IDE / agent using dot-notation naming for navigable discovery:

Local (no API key, no network):

  • ide.detectLayout — find which IDE conventions your repo uses
  • skills.listLocal, skills.readLocal, skills.writeLocal
  • skills.lint — front-matter, token count, broken links, TODO scan, pass / warn / fail checks (scanner h5)
  • skills.flightCheck — Flight Check offline safety scan (injection, exfiltration, secrets, destructive commands, wildcard tools, loop hazards); same rules as npx modelbound check
  • skills.checks — deterministic safety/quality checks without full lint (no numeric score)
  • skills.scaffold — create a skill with default scope constraints
  • skills.reviewStatus, skills.reviewRequest, skills.reviewApprove, skills.reviewReject, skills.reviewGate
  • skills.validateFormat — agentskills.io compliance
  • skills.convert — translate between IDE formats (e.g. Cursor → Claude)
  • skills.diff — compare a local skill with its cloud counterpart

Cloud (with MODELBOUND_API_KEY):

  • cloud.pullSkill, cloud.pushSkill, cloud.search
  • cloud.listSkills — now accepts ai_type and source_platform filters; every row includes ai_type, source_platform, source_path, and repo
  • cloud.resourceTree — returns the team's full hierarchy grouped by platform → top-level dir (.claude/skills, .cursor/rules, .kiro/steering, …) → files. Use this before cloud.listSkills when an orchestrator needs to map context before loading.
  • cloud.installMarketplaceSkill
  • optimization.health

Resource hierarchy

Orchestrators that juggle multiple AI platforms can call cloud.resourceTree once to get a complete map of available skills, rules, hooks, steering files, and system prompts — grouped exactly how each platform expects them on disk. Pair it with the new ai_type / source_platform filters on cloud.listSkills to load only the slice you need. See examples/resource-tree.ts.

The cloud tools are a thin JSON-RPC proxy to mcp.modelbound.co. All business logic stays server-side; this repo never touches your data or secrets.

Migration from 0.1.x — old snake_case names (detect_ide_layout, pull_skill, …) were removed in 0.2.0. The hosted ModelBound MCP server still accepts both forms forever for backward compatibility.

Anti-slop (0.4.x) — trust scanner bumped to h5 with scope-limit, unbounded-wording, dependency, and refactor findings. skills.readLocal now returns checks, scanner_version, review_state, and review_meta. Override default scope limits via .modelbound/task-budgets.json. Use skills.reviewGate in CI to block unapproved skills.

Install

bash
npx modelbound-mcp

Or install globally:

bash
npm i -g modelbound-mcp

Use as an MCP server

Cursor (.cursor/mcp.json)

json
{  "mcpServers": {    "modelbound": {      "command": "npx",      "args": ["-y", "modelbound-mcp"],      "env": { "MODELBOUND_API_KEY": "mb_live_..." }    }  }}

MODELBOUND_API_KEY is optional. Without it, local tools still work.

See examples/ for Claude Desktop, Kiro, Windsurf, and VS Code configs.

Use as a CLI

bash
modelbound-mcp detect                                  # which IDE layouts exist here?modelbound-mcp ls                                      # list every skill filemodelbound-mcp lint .cursor/rules/                     # lint a directorymodelbound-mcp lint .codex/skills/                     # lint Codex skillsmodelbound-mcp validate ./SKILL.md                     # agentskills.io compliancemodelbound-mcp convert --from cursor --to claude ./rule.mdc > out.md

Tests

bash
npm test              # unit tests (registry parity, checks, review, harness)npm run smoke         # local MCP tools + CLI subcommands (+ cloud if MODELBOUND_API_KEY set)npm run test:e2e      # offline anti-slop / review lifecycle

CLI vs MCP tool mapping: docs/PARITY.md.

Contributing

We want help. Specifically:

  • New IDE adapters — Zed, Aider, Continue, JetBrains AI, Cline. See CONTRIBUTING.md for the ~50 line recipe.
  • Linter rules — token estimation accuracy, dead-link detection, format-specific gotchas.
  • Format converters — fidelity improvements between adapter pairs.

Browse good first issues and the roadmap.

Related projects

ProjectDescription
ModelBound CLI · npmTerminal + CI for token optimization, skill pipeline, and version management
Cursor Extension · MarketplaceVS Code/Cursor extension for rules sync and MCP bridge
Cursor PluginCursor slash commands for pipeline, safety checks, and versions
Claude Code PluginClaude Code plugin for pipeline, hooks, and skill sync
Dev PacksOpen-source curated AI context packs for engineering teams

Also on Smithery (stdio via npx modelbound-mcp) and the MCP Registry. Install hub: modelbound.co/connect

License

MIT © ModelBound

来源:README.md,提交 0a56c12

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.1.2最新Sep 16, 2026

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