claude-prompts

The portable workflow layer beside your AI coding harness.

Quick Start · What You Get · Compose Workflows · Run Anywhere · Docs

What your AI client gives you — and what this server adds

Your client already does	This server adds
Run a prompt	Compose prompts with validation, reasoning guidance, and formatting in one expression
Single-shot skills	Multi-step workflows that thread context between steps
Execute subagents	Hand off mid-chain steps to agents with full workflow context
Client-native skill format	Author once as YAML, export to any client with skills:export
Manual prompt writing	Versioned templates with hot-reload, rollback, and history
Trust the output	Validate output between steps: self-evaluation and shell commands

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 /commands already 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.

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Quick Start

Claude Code (Recommended)

# Add marketplace (first time only)
/plugin marketplace add minipuft/minipuft-plugins

# Install
/plugin install claude-prompts@minipuft

# Try it
>>tech_evaluation_chain library:'zod' context:'API validation'

Load plugin from local source for development:

git clone https://github.com/minipuft/claude-prompts-mcp ~/Applications/claude-prompts-mcp
cd ~/Applications/claude-prompts-mcp/server && npm install && npm run build
claude --plugin-dir ~/Applications/claude-prompts-mcp

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:

[features]
hooks = true

Then install the plugin:

codex plugin marketplace add https://github.com/minipuft/minipuft-plugins.git
codex plugin add codex-prompts@minipuft

Restart Codex, run /hooks to review the plugin hooks, then try >>tech_evaluation_chain library:'zod' context:'API validation'.

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More Client Setups

Claude Desktop

Option A: GitHub Release (recommended)

1. Download claude-prompts-{version}.mcpb from Releases
2. Drag into Claude Desktop Settings → MCP Servers
3. 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

{
  "mcpServers": {
    "claude-prompts": {
      "command": "npx",
      "args": ["-y", "claude-prompts@latest", "--client", "claude-code"]
    }
  }
}

Restart Claude Desktop and test: >>research_chain topic:'remote team policies'

Client setup: VS Code, Cursor, and other MCP-only clients use the manual configuration guide below.

Plugin installers (recommended where available; adds hooks):

# OpenCode (full hooks)
npm install -g opencode-prompts && opencode-prompts install

# Gemini CLI (partial hooks)
gemini extensions install https://github.com/minipuft/gemini-prompts

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):

git clone https://github.com/minipuft/claude-prompts-mcp.git
cd claude-prompts-mcp/server && npm install && npm run build && npm test

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. See Custom Resources Guide.

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What You Get

Four primitives you author, version, and compose. The bundled set ships 51 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.

Primitive	Symbol	What it is	Example
Prompt template	>>	Versioned YAML with named arguments; hot-reload on save	>>review target:'src/auth/'
Gate	::	Validation criterion the AI checks its own output against; blocking or advisory; can shell-verify	:: 'cite sources' · :: verify:"npm test"
Framework	@	Reasoning framework that shapes how the AI works through the problem; plug in your own or use built-ins like @ReACT, @5W1H, or the project's own @CAGEERF scaffold (Frameworks Guide)	@ReACT · @your_framework
Style	#	Output formatting and tone	#analytical · #procedural

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:

Tool	Purpose
prompt_engine	Execute prompts with frameworks and validation
resource_manager	Create, update, version, and roll back resources
system_control	Status, analytics, framework switching

Most users invoke these via >> syntax in conversation; hooks construct the actual calls. For programmatic MCP clients calling tools directly, see MCP Tools Reference.

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Compose Workflows

How to write a chain

>>review target:'src/auth/' @ReACT :: 'cite sources'
  --> security_scan :: verify:"npm test"
  ==> implementation

Read top-to-bottom:

• >>review target:'src/auth/' runs the review prompt against your auth folder.
• @ReACT overlays 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 pass npm test before producing output.
• ==> implementation hands 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.

A gate catches a missing field, the model corrects itself, and the chain passes. Recorded on haiku, the cheapest model.

Two patterns extend the basic syntax. Chains also support context threading between steps and agent handoffs. See Chains Lifecycle and MCP Tools Reference.