
Claude Prompts Mcp
io.github.minipuft由 GitHub 帳號 minipuft 發布v4.0.1更新於 Oct 27, 2026
Reusable prompt templates, multi-step workflow chains, and quality gates for any MCP client.
發布方自己的服務:Claude Platform Docs
概覽
本機 MCP 伺服器,為 AI 程式開發客戶端提供可重複使用的提示詞範本、多步驟工作流程鏈、驗證閘門與推理框架。
- 可以做什麼
- 執行具名引數、推理框架與輸出風格的版本化提示詞範本
- 將提示詞串成多步驟工作流程,在步驟間傳遞脈絡並交接給客戶端代理
- 在步驟之間以自我評估閘門或 shell 指令驗證輸出,支援重試與迴圈預設
- 透過資源管理工具建立、編輯、版本化並回復提示詞、閘門與框架
- 查看伺服器狀態、分析資料並切換框架
- 將提示詞匯出為客戶端原生技能
- 適用情境
- 適合反覆撰寫相同提示詞、需要執行多步驟工作流程,或想與團隊共用可重複使用提示詞與驗證規則的人。若客戶端內建指令已能滿足需求,或你想要無程式碼的提示詞庫,則不必安裝。
- 執行需求
- 以 npm 套件(npx claude-prompts)或自包含桌面安裝包在本機透過 stdio 執行;npm 方式需要 Node.js。部分客戶端可透過外掛安裝器取得鉤子,自訂工作區路徑可用 MCP_RESOURCES_PATH 指定。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Claude Prompts Mcp,將其新增到工作區。
- 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
Claude Prompts
The portable workflow layer beside your AI coding harness.
Your client executes with its own tools, agents, and context.
Claude Prompts adds reusable prompt resources, composable chains, validation gates, and client-native skill export.
[Set up the Claude Code plugin] [Set up the experimental Codex plugin]
Quick Start · What You Get · Compose Workflows · Run Anywhere · Docs
What your AI client gives you — and what this server adds
Is this for me?
- Use this if you write the same prompts repeatedly, run multi-step workflows, or want to share reusable prompts with a team.
- Skip if your client's built-in
/commandsalready handle what you need, or you're looking for a no-code prompt library. - Works with Claude Code, Claude Desktop, Cursor, OpenCode, Gemini CLI, Codex, Windsurf, and Zed. Plugin installers add hooks (chain tracking, gate enforcement, state preservation) for Claude Code, OpenCode, Gemini CLI, and Codex (experimental); other clients run MCP-only.
Quick Start
Claude Code (Recommended)
Development setup
Load plugin from local source for development:
Edit hooks/prompts → restart Claude Code. Edit TypeScript → rebuild first.
Codex (Experimental)
Codex hooks require Codex CLI 0.117 or later and are unavailable on Windows. See the codex-prompts requirements for Python and Node.js prerequisites.
Enable hooks in ~/.codex/config.toml:
Then install the plugin:
Restart Codex, run /hooks to review the plugin hooks, then try >>tech_evaluation_chain library:'zod' context:'API validation'.
More Client Setups
Claude Desktop
Option A: GitHub Release (recommended)
- Download
claude-prompts-{version}.mcpbfrom Releases - Drag into Claude Desktop Settings → MCP Servers
- Done
The .mcpb bundle is self-contained (~5MB); no npm required.
Option B: NPX (auto-updates)
Add to your config file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
Restart Claude Desktop and test: >>research_chain topic:'remote team policies'
Other clients: VS Code · Cursor · OpenCode · Gemini CLI · Windsurf · Zed · From Source
Client setup: VS Code, Cursor, and other MCP-only clients use the manual configuration guide below.
Plugin installers (recommended where available; adds hooks):
Manual config for VS Code, Cursor, OpenCode (no hooks), Gemini CLI (no hooks), Codex (no plugin hooks), Windsurf, and Zed: see Client Integration Guide for per-client config locations, JSON examples, and --client preset matrix. Client Capabilities Reference covers profile mapping and limits.
From source (developers):
Point your MCP config to server/dist/index.js. Transport: --transport=stdio (default) or --transport=streamable-http.
Custom resources: --init=~/my-prompts scaffolds a starter workspace: three example prompts plus config.jsonc. Edit them (YAML schema), or have your AI author new prompts, gates, and frameworks via resource_manager. Point MCP_RESOURCES_PATH at an existing workspace if you already have one in the right shape. Resources that belong to one repository go in .claude-prompts/ at its root (cpm init --project scaffolds it) and load above your workspace over STDIO. See Custom Resources Guide.
What You Get
Four primitives you author, version, and compose. The bundled set ships 52 prompts across 9 categories — a starting library, not the ceiling: your AI writes new prompts and chains through resource_manager as it works, so the set grows around what you actually do. All hot-reloadable, all versioned with rollback.
Prompts, gates, and frameworks are managed through the resource_manager tool. Your AI creates, edits, versions, and rolls them back through MCP, no file editing required. Styles are managed with the bundled cpm CLI. Failed gate checks can retry automatically or pause for your decision (Gates Guide). Build your first primitive: Prompt Authoring Tutorial.
The Three Tools
Everything above reaches your client through three MCP tools:
Most users invoke these via >> syntax in conversation; hooks construct the actual calls. For programmatic MCP clients calling tools directly, see MCP Tools Reference.
Compose Workflows
How to write a chain
Read top-to-bottom:
>>review target:'src/auth/'runs thereviewprompt against your auth folder.^ReACToverlays the ReACT reasoning framework on this step.:: 'cite sources'adds a gate the AI must satisfy (cite sources, or retry).--> security_scan :: verify:"npm test"chains to step 2, which must passnpm testbefore producing output.==> implementationhands the final step off to a client-native agent (a subagent in Claude Code).
review ships with the server; security_scan and implementation stand in for prompts you write.
Validation runs between steps, not only at the end. For the full operator grammar and examples, see MCP Tools Reference.
No video player here? Open the GIF.
[One Claude Code session, with a side panel showing what the hooks and the server do: npm test fails, >>status is routed by the hook, resource_manager creates a prompt, a two-step chain runs it under ^ReACT, the server runs npm test as the gate, and the review step approves the result]Recorded live in Claude Code on Sonnet, sped up, nothing re-ordered or retyped. The side panel is a second recording of the same moments, shown while the session pauses: what each hook did and the server's own npm test run for the gate. The tests are red, the AI authors a prompt through resource_manager, a two-step chain implements under ^ReACT, the verify:"npm test" gate passes, and review approves. Replay the source yourself: asciinema play assets/demos/src/hero/hero.cast (recorder and storyboard beside it).
Two patterns extend the basic syntax. Chains also support context threading between steps and agent handoffs. See Chains Lifecycle and MCP Tools Reference.
See the output: tech evaluation chain with context7 research
[Tech evaluation chain researching Zod via context7, producing a scored assessment table with security, performance, DX, integration, and ecosystem ratings]
Context7 fetches live library docs mid-chain. The final output is a structured assessment with sources.
Verification Loops
Ground-truth validation via shell commands. The AI keeps iterating until tests pass:
Implements, runs the test, reads failures, fixes, retries. Spawns a fresh context after repeated failures to avoid context rot.
implement-feature stands for your own prompt: :: verify attaches to any of them.
For autonomous test-fix cycles with context-rot prevention: Ralph Loops Guide.
Judge Mode
Let the AI pick the right resources for the task:
Analyzes available templates, reasoning frameworks, validation rules, and styles, then recommends the best combination. You confirm before it runs. For scoring and overrides see Judge Mode Guide.
Run Anywhere
Author workflows as YAML templates. Export as native skills to your client.
The review prompt becomes a /review Claude Code skill. validate_work becomes /validate_work. Same source, native experience; no MCP call required at runtime.
Compiles to native skill packages for Claude Code, Cursor, Codex and OpenCode. npm run skills:diff flags when exports drift from source. Configuration, supported clients, and drift detection: Skills Sync Guide.
With Hooks
Without hooks, you're calling the three MCP tools explicitly (the LLM constructs each call). With hooks, the operators work in conversation: >>, -->, ==>, :: feel native rather than mediated, and workflow state survives across LLM turns and context compaction.
What hooks unlock:
Hooks ship with the plugin install. Full support on Claude Code (this repo) and OpenCode; partial on Gemini CLI; experimental on Codex, where Codex hooks are off by default and each install requires a one-time /hooks trust review. Other clients get the three MCP tools but no hook-driven behaviors. Detail: hooks/README.md.
How It Works
Command with operators → server parses and injects resources (framework, gates, style) → client executes the rendered prompt and self-evaluates against the gates → router decides: next step on pass, retry on fail, return on done.
Full request lifecycle, pipeline stages, and subsystem diagrams: Architecture Overview.
Documentation
Choose a guide based on what you want to do: learn by building, complete a task, look up syntax, or understand the design.
Quick jumps: Build your first prompt · Chains lifecycle · MCP Tools reference · Architecture overview · Troubleshooting
Contributing
The build produces a self-contained bundle. server/dist/ is gitignored, and CI builds fresh from source.
See CONTRIBUTING.md for workflow details.
License
來源:README.md,提交 a4dbed4
工具
0版本歷史
1- v4.0.1最新Sep 16, 2026
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遠端 MCP 伺服器,讓助理搜尋並閱讀 Claude 平台文件與 API 參考。

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