Claude Prompts MCP Server

Hot-reloadable prompts, structured reasoning, and chain workflows for your AI assistant.

Quick Start • What You Get • Syntax • Docs

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Why

Stop copy-pasting prompts. This server turns your prompt library into a programmable engine:

• Version Control — Prompts are YAML + templates in git. Track changes, review diffs.
• Hot Reload — Edit a template, run it immediately. No restarts.
• Structured Execution — Parses operators, injects methodology, enforces quality gates.

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How It Works

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flowchart TB
    classDef actor fill:#0f172a,stroke:#cbd5e1,stroke-width:1.5px,color:#f8fafc;
    classDef server fill:#111827,stroke:#fbbf24,stroke-width:1.8px,color:#f8fafc;
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    classDef clientbg fill:#1a0a24,stroke:#a855f7,stroke-width:1.8px,color:#f8fafc;
    classDef decision fill:#fef3c7,stroke:#f59e0b,stroke-width:1.6px,color:#78350f;

    linkStyle default stroke:#94a3b8,stroke-width:2px

    User["1. User sends command"]:::actor
    Example[">>analyze @CAGEERF :: 'cite sources'"]:::actor
    User --> Example --> Parse

    subgraph Server["MCP Server"]
        direction TB
        Parse["2. Parse operators"]:::process
        Inject["3. Inject framework + gates"]:::process
        Render["4. Render prompt"]:::process
        Decide{"6. Route verdict"}:::decision
        Parse --> Inject --> Render
    end
    Server:::server

    subgraph Client["Claude (Client)"]
        direction TB
        Execute["5. Run prompt + check gates"]:::client
    end
    Client:::clientbg

    Render -->|"Prompt with gate criteria"| Execute
    Execute -->|"Verdict + output"| Decide

    Decide -->|"PASS → render next step"| Render
    Decide -->|"FAIL → render retry prompt"| Render
    Decide -->|"Done"| Result["7. Return to user"]:::actor

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The feedback loop: You send a command with operators → Server parses and injects methodology/gates → Claude executes and self-evaluates → Server routes: next step (PASS), retry (FAIL), or return result (done).

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Quick Start

Claude Code (Recommended)

/plugin install claude-prompts@minipuft

The plugin adds hooks that fix common issues:

Problem	Hook Fix
Model ignores >>analyze	Detects syntax, suggests correct MCP call
Chain step forgotten	Injects [Chain] Step 2/5 - continue
Gate review skipped	Reminds GATE_REVIEW: PASS|FAIL

Raw MCP works, but models sometimes miss the syntax. The hooks catch that. → hooks/README.md

Other MCP Clients

NPM (Claude Desktop, generic clients)

Add to your MCP config (claude_desktop_config.json, .cursor/mcp.json, etc.):

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

Restart your client, then test: resource_manager(resource_type:"prompt", action:"list")

Cursor 1-click install

From Source

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

Then point your config to server/dist/index.js.

Custom Resources

Use your own prompts without cloning:

{
  "mcpServers": {
    "claude-prompts": {
      "command": "npx",
      "args": ["-y", "claude-prompts@latest"],
      "env": {
        "MCP_RESOURCES_PATH": "/path/to/your/resources"
      }
    }
  }
}

Your resources directory can contain: prompts/, gates/, methodologies/, styles/.

Override Method	Example
All resources	MCP_RESOURCES_PATH=/path/to/resources
Just prompts	MCP_PROMPTS_PATH=/path/to/prompts
CLI flag (dev)	--prompts=/path/to/prompts

Priority: CLI flags > individual env vars > MCP_RESOURCES_PATH > package defaults.

See CLI Configuration for all options.

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What You Get

🔥 Hot Reload

Edit prompts, test immediately. Better yet—ask Claude to fix them:

User: "The code_review prompt is too verbose"
Claude: resource_manager(action:"update", id:"code_review", ...)
User: "Test it"
Claude: prompt_engine(command:">>code_review")  # Uses updated version instantly

🔗 Chains

Break complex tasks into steps with -->:

analyze code --> identify issues --> propose fixes --> generate tests

Each step's output flows to the next. Add quality gates between steps.

🧠 Frameworks

Inject structured thinking patterns:

@CAGEERF Review this architecture    # Context → Analysis → Goals → Execution → Evaluation → Refinement
@ReACT Debug this error              # Reason → Act → Observe loops

🛡️ Gates

Quality criteria Claude self-checks:

Summarize this :: 'under 200 words' :: 'include key statistics'

Failed gates can retry automatically or pause for your decision.

✨ Judge Selection

Let Claude pick the right tools:

%judge Help me refactor this codebase

Claude analyzes available frameworks, gates, and styles, then applies the best combination.

📜 Version History

Every update is versioned. Compare, rollback, undo:

resource_manager(action:"history", id:"code_review")
resource_manager(action:"rollback", id:"code_review", version:2, confirm:true)

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Syntax Reference

Symbol	Name	What It Does	Example
>>	Prompt	Execute template	>>code_review
-->	Chain	Pipe to next step	step1 --> step2
@	Framework	Inject methodology	@CAGEERF
::	Gate	Add quality criteria	:: 'cite sources'
%	Modifier	Toggle behavior	%clean, %judge
#	Style	Apply formatting	#analytical

Modifiers:

• %clean — No framework/gate injection
• %lean — Gates only, skip framework
• %guided — Force framework injection
• %judge — Claude selects best resources

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Using Gates

# Inline (quick)
Research AI :: 'use recent sources' --> Summarize :: 'be concise'

# With framework
@CAGEERF Explain React hooks :: 'include examples'

# Programmatic
prompt_engine({
  command: ">>code_review",
  gates: [{ name: "Security", criteria: ["No hardcoded secrets"] }]
})

Severity	Behavior
Critical/High	Must pass (blocking)
Medium/Low	Warns, continues (advisory)

See Gates Guide for full schema.

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Configuration

Customize via server/config.json:

Section	Setting	Default	Description
prompts	directory	prompts	Prompts directory (hot-reloaded)
frameworks	injection.systemPrompt	enabled	Auto-inject methodology guidance
gates	definitionsDirectory	gates	Quality gate definitions
execution	judge	true	Enable %judge resource selection

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The Three Tools

Tool	Purpose
prompt_engine	Execute prompts with frameworks and gates
resource_manager	CRUD for prompts, gates, methodologies
system_control	Status, analytics, health checks

prompt_engine(command:"@CAGEERF >>analysis topic:'AI safety'")
resource_manager(resource_type:"prompt", action:"list")
system_control(action:"status")

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Documentation

• MCP Tooling Guide — Full command reference
• Prompt Authoring — Template syntax and schema
• Chains — Multi-step workflows
• Gates — Quality validation
• Architecture — System internals

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Contributing

cd server
npm install && npm run build
npm test
npm run validate:all  # Full CI check

See CONTRIBUTING.md for details.

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License

MIT