Modelbound Mcp

io.github.ModelBound由 GitHub 帳號 ModelBound 發布v0.1.2更新於 Nov 3, 2026

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

概覽

AI 產生的概覽

以本機優先的 agent 技能檔案 MCP 伺服器:偵測 IDE 佈局,列出、讀取、寫入、檢查、安全掃描、驗證、轉換與比對技能,並可選擇性與 ModelBound 雲端同步。

可以做什麼
  • 偵測儲存庫使用的 IDE 慣例,並列出、讀取或寫入本機技能檔案
  • 檢查技能的 front-matter、token 數量、失效連結與 TODO,並離線掃描注入、資料外洩、密鑰與破壞性指令等風險
  • 依 agentskills.io 規範驗證技能,在 IDE 格式之間轉換,並依預設範圍限制產生新技能
  • 執行審核流程(查看狀態、申請、核准、駁回、門檻),可在 CI 中阻擋未核准的技能
  • 設定 API 金鑰後:拉取、推送、搜尋、列出與安裝市集技能,檢視團隊資源樹並檢查最佳化健康度
適用情境
適合在儲存庫中維護 agent 技能、規則或 steering 檔案,並在 Cursor、Claude、Codex、Kiro、Windsurf、VS Code 或 Amazon Q 之間切換的情境,或希望在技能被使用前先做檢查與安全掃描。只有團隊把技能存放在 ModelBound 時,雲端工具才有意義。
執行需求
透過 stdio 在本機執行,通常使用 npx modelbound-mcp 或全域安裝 npm 套件,因此需要 Node.js。本機工具不需帳號或網路。雲端同步工具需要環境變數 MODELBOUND_API_KEY,此金鑰為選用。
安裝前請注意
此伺服器可寫入本機技能檔案;設定 API 金鑰後還能將技能推送到 ModelBound 雲端並安裝市集技能,變更可能影響團隊共用內容。API 金鑰屬於機密,不要放進共用設定。雲端工具會把請求轉送到託管的 ModelBound 端點,使用時技能內容會離開本機。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Modelbound Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

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

來源:README.md,提交 0a56c12

工具

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版本歷史

1
  1. v0.1.2最新Sep 16, 2026

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