[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6D39PRQ7XFJ7FB6FTKBF9KH":3,"skill-same:01M6D39PRQ7XFJ7FB6FTKBF9KH":72},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":30,"linkOnly":31,"markdownContent":32,"markdownBody":33,"frontMatter":34,"refName":35,"commitSha":36,"skillDirectory":37,"forksCount":38,"repositoryHtmlUrl":39,"repositoryHomepageUrl":6,"ownerHtmlUrl":40,"ownerBlogUrl":41,"ownerDescription":42,"updatedAt":43,"install":44,"resources":57},"01M6D39PRQ7XFJ7FB6FTKBF9KH","create-mcp",null,"Create new MCP integration with guided wizard","hemory\u002Famp-legacy-do-not-use","hemory","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F21179881?v=4","01M6D31HFJ391DN8N0JP8AQGFE","Hemory Phifer","01M6D31HKXVTEN27AT6R4PP2ZJ",3,"MIT","https:\u002F\u002Fgithub.com\u002Fhemory\u002Famp-legacy-do-not-use\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fcreate-mcp\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29],"MCP","create","create mcp","integration","MCP Integration","wizard","2026-11-10 10:12:30",false,"---\nname: create-mcp\ndescription: Create new MCP integration with guided wizard\n---\n\n## What This Command Does\n\n**In plain English:** A guided wizard that helps you create and integrate an MCP server into Amp. No coding knowledge required - you describe what you want, we build it together.\n\n**When to use it:**\n- You want to connect Amp to an external service (calendar, email, CRM, API)\n- You have data somewhere that would be useful in Amp\n- You want to automate interactions with a tool you use regularly\n\n**How to run it:**\n```\n\u002Fcreate-mcp                    # Starts the wizard from the beginning\n\u002Fcreate-mcp \"calendar\"         # Jumps ahead with a service hint\n```\n\n---\n\n## Why MCP Matters: Probabilistic AI vs Deterministic Tools\n\n### The Problem with AI Alone\n\nAI models like Claude are fundamentally **probabilistic** - they generate responses by predicting the most likely next token based on patterns in their training data. This is powerful for reasoning and language, but dangerous for facts:\n\n| Question | Without MCP | With MCP |\n|----------|-------------|----------|\n| \"What's on my calendar today?\" | *\"I don't have access to your calendar, but typically...\"* | **Queries actual calendar, returns real events** |\n| \"What are our top support tickets this week?\" | *\"Based on typical patterns, around 10-15...\"* | **Queries Zendesk: \"32 tickets, 12 P0, avg response time 2.3hrs\"** |\n| \"Did Sarah email about the roadmap?\" | *\"I can't access your email...\"* | **Searches Gmail, finds 3 matching threads** |\n\nWithout MCP, AI can only:\n- Guess based on general knowledge\n- Hallucinate plausible-sounding but wrong answers\n- Admit it doesn't have access\n\n### What MCP Actually Does\n\nMCP (Model Context Protocol) provides **guardrails and structure** for AI interactions with external systems:\n\n```\n┌─────────────────────────────────────────────────────────────┐\n│                    YOUR QUESTION                            │\n│         \"What features are customers using most?\"           │\n└─────────────────────────────────────────────────────────────┘\n                              │\n                              ▼\n┌─────────────────────────────────────────────────────────────┐\n│                    AI REASONING                             │\n│  \"I need support ticket data. I have a Zendesk MCP tool    │\n│   called `get_ticket_stats`. Let me call it...\"            │\n└─────────────────────────────────────────────────────────────┘\n                              │\n                              ▼\n┌─────────────────────────────────────────────────────────────┐\n│                    MCP TOOL CALL                            │\n│  Tool: get_feature_usage                                    │\n│  Input: { \"days\": 30, \"limit\": 10 }                        │\n│  ─────────────────────────────────────────────────────────  │\n│  │ GUARDRAILS:                                          │  │\n│  │ ✓ Defined input schema - can't send bad data         │  │\n│  │ ✓ Authenticated connection - uses real credentials   │  │\n│  │ ✓ Structured output - returns consistent format      │  │\n│  │ ✓ Deterministic - same query = same results          │  │\n│  └──────────────────────────────────────────────────────┘  │\n└─────────────────────────────────────────────────────────────┘\n                              │\n                              ▼\n┌─────────────────────────────────────────────────────────────┐\n│                    REAL DATA RESPONSE                       │\n│  { \"features\": [                                            │\n│    { \"name\": \"Dashboard\", \"usage\": 89% },                   │\n│    { \"name\": \"Reports\", \"usage\": 67% },                     │\n│    { \"name\": \"Guides\", \"usage\": 45% }                       │\n│  ]}                                                         │\n└─────────────────────────────────────────────────────────────┘\n                              │\n                              ▼\n┌─────────────────────────────────────────────────────────────┐\n│                    AI SYNTHESIS                             │\n│  \"Your top 3 features by usage are Dashboard (89%),        │\n│   Reports (67%), and Guides (45%). Dashboard dominates -   │\n│   consider investing more there.\"                          │\n└─────────────────────────────────────────────────────────────┘\n```\n\n### The Key Insight\n\nMCP doesn't make AI smarter - it gives AI **reliable ways to get real data**. The AI still does reasoning, synthesis, and explanation. But the facts come from deterministic tool calls, not probabilistic generation.\n\n| Aspect | Probabilistic (AI alone) | Deterministic (MCP) |\n|--------|--------------------------|---------------------|\n| Data source | Training patterns | Live API calls |\n| Accuracy | Plausible but unreliable | Exact (from source) |\n| Freshness | Stale (training cutoff) | Real-time |\n| Consistency | May vary per query | Same query = same data |\n| Guardrails | None | Schema validation, auth, error handling |\n\n---\n\n## Entry Point\n\n### If no arguments provided:\n\n```\n? **MCP Server Creation Wizard**\n\nMCP (Model Context Protocol) lets Amp connect to external tools and services. Instead of guessing or saying \"I don't have access\", AI can query real data and give you accurate answers.\n\n**The difference MCP makes:**\n- ❌ Without: \"I'd estimate you have around 10-15 support tickets...\"\n- ✅ With: \"Zendesk shows 32 tickets, 12 high priority, avg response time 2.3hrs\"\n\n**Examples of what you can build:**\n- ? Calendar → \"What meetings do I have tomorrow? Who's attending?\"\n- ? Email → \"Find emails from Sarah about the Q1 roadmap\"\n- ? Slack → \"What did #product-team discuss today?\"\n- ? Analytics → \"Show me feature adoption for our enterprise tier\"\n- ? Any API → If it has an API, we can probably connect it\n\n**Benefits:**\n- Real data, not AI guessing\n- Guardrails prevent hallucination\n- Live queries, not stale training data\n- Structured tools with validation\n\n**This wizard will:**\n1. Help you describe what you want to connect\n2. Design the integration together\n3. Generate the MCP server code\n4. Integrate it into Amp\n5. Update all documentation so future sessions know how to use it\n\nReady to get started? **What would you like to connect Amp to?**\n\n(Just describe it in plain English — e.g., \"my Google Calendar\", \"Notion database\", \"company CRM\")\n```\n\n### If service hint provided:\n\nSkip education and jump to Phase 1 with the hint as starting context.\n\n---\n\n## Phase 1: Understand the Connection\n\n### Goal: Get clarity on what service and what data\n\nAsk these questions (adapt based on what's already known):\n\n**Question 1: Service identification**\n```\nWhat service or tool do you want to connect?\n\nExamples:\n- A specific app (Google Calendar, Notion, Salesforce)\n- A type of data (my emails, my tasks, my documents)\n- An API you have access to\n\nYour answer:\n```\n\n**Question 2: Authentication**\n```\nHow do you currently access this service?\n\n1. I log in with username\u002Fpassword\n2. I have an API key\n3. It uses OAuth (Google, Microsoft login)\n4. It's a local file or database\n5. Something else\n\nThis helps me understand what authentication we'll need.\n```\n\n**Question 3: Data of interest**\n```\nWhat specific information do you want Amp to access?\n\nBe specific about:\n- What types of data (events, messages, records)\n- What you'd want to read vs. write\n- Any specific fields that matter most\n\nExample: \"I want to see my calendar events - title, time, attendees. Just reading, no need to create events.\"\n```\n\n**Question 4: Use cases**\n```\nHow would you actually use this in practice?\n\nGive me 2-3 example questions or commands you'd want to ask:\n- \"Show me today's meetings\"\n- \"Find emails from [person] about [topic]\"\n- \"What's the status of [account]?\"\n\nThis shapes what tools we'll build.\n```\n\n### After Phase 1, summarize:\n\n```\n**Understood. Here's what we're building:**\n\n? **Service:** [service name]\n? **Auth method:** [auth type]\n? **Data access:** [read\u002Fwrite + what data]\n? **Primary use cases:**\n1. [use case 1]\n2. [use case 2]\n3. [use case 3]\n\nDoes this capture what you want? (yes \u002F let me clarify)\n```\n\n---\n\n## Phase 2: Design the Tools\n\n### Goal: Define the specific MCP tools to build\n\nBased on use cases, propose tool designs:\n\n```\n**Proposed MCP Tools**\n\nBased on your use cases, here's what I suggest building:\n\n| Tool Name | What It Does | Example Usage |\n|-----------|--------------|---------------|\n| `[tool_1]` | [description] | \"[natural language example]\" |\n| `[tool_2]` | [description] | \"[natural language example]\" |\n| `[tool_3]` | [description] | \"[natural language example]\" |\n\n**Input parameters for each:**\n\n### `[tool_1]`\n- `param_1` (required): [description]\n- `param_2` (optional): [description]\n\n### `[tool_2]`\n...\n\n**Questions:**\n1. Do these tools cover your use cases?\n2. Should any tool do more or less?\n3. Are there additional scenarios I missed?\n```\n\n### Iterate until user confirms design\n\nKeep refining based on feedback. Ask focused questions:\n- \"Should [tool] also support [capability]?\"\n- \"What happens if [edge case]?\"\n- \"Do you need to filter by [field]?\"\n\n### Confirm before implementation:\n\n```\n**Final Tool Design**\n\nWe're building an MCP server called `[server-name]` with:\n\n| Tool | Purpose | Inputs |\n|------|---------|--------|\n| [tool] | [purpose] | [inputs summary] |\n\n**Authentication:** [method + what user needs to provide]\n**Configuration:** [any env vars or config needed]\n\nReady to build? (yes \u002F let me adjust)\n```\n\n---\n\n## Phase 3: Implementation\n\n### Goal: Generate the MCP server code\n\n**Step 3.1: Create the server file**\n\nGenerate Python code following the pattern in `core\u002Fmcp\u002Fwork_server.py`:\n\n```python\n#!\u002Fusr\u002Fbin\u002Fenv python3\n\"\"\"\nMCP Server for [Service Name]\n[Brief description of what this server does]\n\nTools:\n- [tool_1]: [description]\n- [tool_2]: [description]\n\"\"\"\n\nimport os\nimport json\nimport logging\nfrom typing import Dict, List, Optional, Any\nfrom datetime import datetime\n\nfrom mcp.server import Server, NotificationOptions\nfrom mcp.server.models import InitializationOptions\nimport mcp.server.stdio\nimport mcp.types as types\n\n# Set up logging\nlogging.basicConfig(level=logging.INFO)\nlogger = logging.getLogger(__name__)\n\n# Configuration from environment\n[RELEVANT_CONFIG_VARS]\n\n# ============================================================================\n# SERVICE CLIENT\n# ============================================================================\n\nclass [ServiceName]Client:\n    \"\"\"Client for interacting with [Service]\"\"\"\n    \n    def __init__(self):\n        [initialization code]\n    \n    [methods for each operation]\n\n# ============================================================================\n# MCP SERVER\n# ============================================================================\n\napp = Server(\"[server-name]-mcp\")\nclient = [ServiceName]Client()\n\n@app.list_tools()\nasync def handle_list_tools() -> list[types.Tool]:\n    \"\"\"List all available tools\"\"\"\n    return [\n        types.Tool(\n            name=\"[tool_name]\",\n            description=\"[tool description]\",\n            inputSchema={\n                \"type\": \"object\",\n                \"properties\": {\n                    [property definitions]\n                },\n                \"required\": [required fields]\n            }\n        ),\n        # ... more tools\n    ]\n\n@app.call_tool()\nasync def handle_call_tool(\n    name: str, arguments: dict | None\n) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:\n    \"\"\"Handle tool calls\"\"\"\n    \n    if name == \"[tool_name]\":\n        [implementation]\n        return [types.TextContent(type=\"text\", text=json.dumps(result, indent=2))]\n    \n    # ... more tool handlers\n    \n    return [types.TextContent(type=\"text\", text=f\"Unknown tool: {name}\")]\n\nasync def _main():\n    \"\"\"Async main entry point\"\"\"\n    logger.info(\"Starting [Service] MCP Server\")\n    \n    async with mcp.server.stdio.stdio_server() as (read_stream, write_stream):\n        await app.run(\n            read_stream,\n            write_stream,\n            InitializationOptions(\n                server_name=\"[server-name]-mcp\",\n                server_version=\"1.0.0\",\n                capabilities=app.get_capabilities(\n                    notification_options=NotificationOptions(),\n                    experimental_capabilities={},\n                ),\n            ),\n        )\n\ndef main():\n    \"\"\"Sync entry point\"\"\"\n    import asyncio\n    asyncio.run(_main())\n\nif __name__ == \"__main__\":\n    main()\n```\n\nSave to: `core\u002Fmcp\u002F[service_name]_server.py`\n\n**Step 3.2: Update requirements**\n\nAdd any new dependencies to `requirements.txt`\n\n**Step 3.3: Create launcher script (if needed)**\n\nCreate `core\u002Fmcp\u002Frun_[service_name].sh`:\n\n```bash\n#!\u002Fbin\u002Fbash\n# Launch [Service] MCP server\ncd \"$(dirname \"$0\")\"\nsource venv\u002Fbin\u002Factivate 2>\u002Fdev\u002Fnull || true\npython [service_name]_server.py\n```\n\nMake executable: `chmod +x run_[service_name].sh`\n\n### Tell user what was created:\n\n```\n**Server Created!** ✅\n\nFiles generated:\n- `core\u002Fmcp\u002F[service_name]_server.py` — The MCP server\n- `requirements.txt` — Updated with dependencies\n\n**Before we integrate, you'll need to:**\n\n[Auth-specific instructions based on Phase 1]\n\nExamples:\n- For API key: \"Add [SERVICE]_API_KEY to your environment or .env file\"\n- For OAuth: \"Run the OAuth setup script: `python core\u002Fmcp\u002Fsetup_[service]_auth.py`\"\n- For local: \"No additional setup needed\"\n\nLet me know when you're ready to integrate.\n```\n\n---\n\n## Phase 4: Integration\n\n### Goal: Connect the MCP server to Amp\n\n**Step 4.1: Update CLAUDE.md**\n\nAdd to the Integration Options section or create new MCP section:\n\n```markdown\n### [Service Name] Integration\n\n**Server:** `core\u002Fmcp\u002F[service_name]_server.py`\n**Purpose:** [what it does]\n\n**Available Tools:**\n\n| Tool | What It Does | Example |\n|------|--------------|---------|\n| `[tool]` | [description] | \"[natural example]\" |\n\n**Configuration Required:**\n- `[ENV_VAR]`: [description]\n\n**Usage examples:**\n- \"[natural language request]\" → uses `[tool]` tool\n- \"[another request]\" → uses `[another_tool]` tool\n```\n\n**Step 4.2: Add MCP Instructions (if not present)**\n\nCheck if CLAUDE.md has mcp_instructions section. If not, add:\n\n```markdown\n\u003Cmcp_instructions>\n### [service-name]-mcp\n\n[Description of the server and when to use it]\n\n**Tools:**\n- `[tool_name]`: [when to use and what it returns]\n\n\u003C\u002Fmcp_instructions>\n```\n\n**Step 4.3: Update System Guide**\n\nAdd to `06-Resources\u002FAmp_System\u002FAmp_System_Guide.md` under Integration Options:\n\n```markdown\n| **[Service]** | [Brief description of capabilities] |\n```\n\nAnd add a new section if significant:\n\n```markdown\n### [Service] MCP Server\n\nServer: `core\u002Fmcp\u002F[service_name]_server.py`\n\n#### Available Tools\n\n| Tool | Purpose |\n|------|---------|\n| `[tool]` | [description] |\n\n#### Usage\n\n[How to use in natural language, what to expect]\n\n#### Configuration\n\n| Variable | Description |\n|----------|-------------|\n| `[ENV_VAR]` | [what it's for] |\n```\n\n---\n\n## Phase 5: Verification\n\n### Goal: Ensure everything is properly connected\n\n**Run verification checklist:**\n\n```\n**Integration Complete!** ?\n\nLet me verify everything is in place:\n\n✅ Server created: `core\u002Fmcp\u002F[service_name]_server.py`\n✅ Dependencies updated: `requirements.txt`\n✅ CLAUDE.md updated with integration docs\n✅ System Guide updated\n\n**To start using it:**\n\n1. Install dependencies (if new ones added):\n   ```\n   pip install -r requirements.txt\n   ```\n\n2. Add your credentials:\n   ```\n   export [ENV_VAR]=\"your-value-here\"\n   ```\n   Or add to your shell config \u002F .env file.\n\n3. Configure Claude Desktop to use the server:\n   Edit `~\u002FLibrary\u002FApplication Support\u002FClaude\u002Fclaude_desktop_config.json`:\n   ```json\n   {\n     \"mcpServers\": {\n       \"[server-name]\": {\n         \"command\": \"python\",\n         \"args\": [\"[full-path]\u002Fcore\u002Fmcp\u002F[service_name]_server.py\"],\n         \"env\": {\n           \"VAULT_PATH\": \"[full-path-to-amp]\"\n         }\n       }\n     }\n   }\n   ```\n\n4. Test it! Try asking:\n   - \"[example natural language query]\"\n\n**Want me to help you test the integration?**\n```\n\n---\n\n## Example Walkthrough\n\n```\nUser: \u002Fcreate-mcp\n\nClaude: [Shows education intro]\n\nUser: I want to connect my Todoist\n\nClaude: Great choice! Let me understand what you need...\n\n[Phase 1 questions]\n\nUser: I want to see my tasks, add new ones, and mark them complete.\n      Example: \"What's on my Todoist today?\" or \"Add 'buy groceries' to Todoist\"\n\nClaude: **Understood. Here's what we're building:**\n\n? **Service:** Todoist\n? **Auth method:** API key (Todoist provides this)\n? **Data access:** Read tasks, create tasks, update task status\n? **Primary use cases:**\n1. \"What's on my Todoist today\u002Fthis week?\"\n2. \"Add [task] to Todoist\"\n3. \"Mark [task] as done in Todoist\"\n\nDoes this capture what you want?\n\nUser: Yes, but also let me filter by project\n\nClaude: Got it! Adding project filtering...\n\n[Phase 2 - Tool design]\n\n**Proposed MCP Tools**\n\n| Tool Name | What It Does |\n|-----------|--------------|\n| `list_tasks` | Get tasks with filters (today, date range, project) |\n| `create_task` | Add a new task to Todoist |\n| `complete_task` | Mark a task as done |\n| `list_projects` | See available projects |\n\n[Continues through phases...]\n```\n\n---\n\n## Behaviors\n\n### Always Do\n- Start with education for new users\n- Confirm understanding before building\n- Generate complete, working code\n- Update ALL documentation (CLAUDE.md, System Guide)\n- Provide clear setup instructions\n- Offer to help test\n\n### Never Do\n- Skip the design phase\n- Generate partial\u002Fplaceholder code\n- Forget to update documentation\n- Assume authentication works without explaining setup\n- Create tools without clear use cases\n\n### If stuck on technical details\n- Search for the service's API documentation\n- Check if an existing Python library handles auth\n- Offer simpler alternatives if complexity is high\n\n---\n\n## Integration Checklist\n\nAfter completion, verify:\n\n- [ ] Server file created in `core\u002Fmcp\u002F`\n- [ ] Requirements.txt updated\n- [ ] CLAUDE.md has integration documentation\n- [ ] System Guide updated with new capabilities\n- [ ] Setup instructions are clear and complete\n- [ ] Example queries provided for testing\n\n### Analytics (Required)\n\n- [ ] Events defined for key tools (e.g., `{tool}_used`)\n- [ ] Added checkbox to `System\u002Fusage_log.md` (Integrations section)\n- [ ] Privacy verified: only tracks that feature was used, not content\n\nSee `.claude\u002Freference\u002Fskill-analytics-checklist.md` for detailed guidance.\n- [ ] User knows how to configure Claude to use the server\n\n---\n\n## Track Usage (Silent)\n\nUpdate `System\u002Fusage_log.md` to mark MCP creation as used.\n\n**Analytics (Silent):**\n\nCall `track_event` with event_name `mcp_created` and properties:\n- (no properties — do NOT include service names)\n\nThis only fires if the user has opted into analytics. No action needed if it returns \"analytics_disabled\".\n","## What This Command Does\n\n**In plain English:** A guided wizard that helps you create and integrate an MCP server into Amp. No coding knowledge required - you describe what you want, we build it together.\n\n**When to use it:**\n- You want to connect Amp to an external service (calendar, email, CRM, API)\n- You have data somewhere that would be useful in Amp\n- You want to automate interactions with a tool you use regularly\n\n**How to run it:**\n```\n\u002Fcreate-mcp                    # Starts the wizard from the beginning\n\u002Fcreate-mcp \"calendar\"         # Jumps ahead with a service hint\n```\n\n---\n\n## Why MCP Matters: Probabilistic AI vs Deterministic Tools\n\n### The Problem with AI Alone\n\nAI models like Claude are fundamentally **probabilistic** - they generate responses by predicting the most likely next token based on patterns in their training data. This is powerful for reasoning and language, but dangerous for facts:\n\n| Question | Without MCP | With MCP |\n|----------|-------------|----------|\n| \"What's on my calendar today?\" | *\"I don't have access to your calendar, but typically...\"* | **Queries actual calendar, returns real events** |\n| \"What are our top support tickets this week?\" | *\"Based on typical patterns, around 10-15...\"* | **Queries Zendesk: \"32 tickets, 12 P0, avg response time 2.3hrs\"** |\n| \"Did Sarah email about the roadmap?\" | *\"I can't access your email...\"* | **Searches Gmail, finds 3 matching threads** |\n\nWithout MCP, AI can only:\n- Guess based on general knowledge\n- Hallucinate plausible-sounding but wrong answers\n- Admit it doesn't have access\n\n### What MCP Actually Does\n\nMCP (Model Context Protocol) provides **guardrails and structure** for AI interactions with external systems:\n\n```\n┌─────────────────────────────────────────────────────────────┐\n│                    YOUR QUESTION                            │\n│         \"What features are customers using most?\"           │\n└─────────────────────────────────────────────────────────────┘\n                              │\n                              ▼\n┌─────────────────────────────────────────────────────────────┐\n│                    AI REASONING                             │\n│  \"I need support ticket data. I have a Zendesk MCP tool    │\n│   called `get_ticket_stats`. Let me call it...\"            │\n└─────────────────────────────────────────────────────────────┘\n                              │\n                              ▼\n┌─────────────────────────────────────────────────────────────┐\n│                    MCP TOOL CALL                            │\n│  Tool: get_feature_usage                                    │\n│  Input: { \"days\": 30, \"limit\": 10 }                        │\n│  ─────────────────────────────────────────────────────────  │\n│  │ GUARDRAILS:                                          │  │\n│  │ ✓ Defined input schema - can't send bad data         │  │\n│  │ ✓ Authenticated connection - uses real credentials   │  │\n│  │ ✓ Structured output - returns consistent format      │  │\n│  │ ✓ Deterministic - same query = same results          │  │\n│  └──────────────────────────────────────────────────────┘  │\n└─────────────────────────────────────────────────────────────┘\n                              │\n                              ▼\n┌─────────────────────────────────────────────────────────────┐\n│                    REAL DATA RESPONSE                       │\n│  { \"features\": [                                            │\n│    { \"name\": \"Dashboard\", \"usage\": 89% },                   │\n│    { \"name\": \"Reports\", \"usage\": 67% },                     │\n│    { \"name\": \"Guides\", \"usage\": 45% }                       │\n│  ]}                                                         │\n└─────────────────────────────────────────────────────────────┘\n                              │\n                              ▼\n┌─────────────────────────────────────────────────────────────┐\n│                    AI SYNTHESIS                             │\n│  \"Your top 3 features by usage are Dashboard (89%),        │\n│   Reports (67%), and Guides (45%). Dashboard dominates -   │\n│   consider investing more there.\"                          │\n└─────────────────────────────────────────────────────────────┘\n```\n\n### The Key Insight\n\nMCP doesn't make AI smarter - it gives AI **reliable ways to get real data**. The AI still does reasoning, synthesis, and explanation. But the facts come from deterministic tool calls, not probabilistic generation.\n\n| Aspect | Probabilistic (AI alone) | Deterministic (MCP) |\n|--------|--------------------------|---------------------|\n| Data source | Training patterns | Live API calls |\n| Accuracy | Plausible but unreliable | Exact (from source) |\n| Freshness | Stale (training cutoff) | Real-time |\n| Consistency | May vary per query | Same query = same data |\n| Guardrails | None | Schema validation, auth, error handling |\n\n---\n\n## Entry Point\n\n### If no arguments provided:\n\n```\n? **MCP Server Creation Wizard**\n\nMCP (Model Context Protocol) lets Amp connect to external tools and services. Instead of guessing or saying \"I don't have access\", AI can query real data and give you accurate answers.\n\n**The difference MCP makes:**\n- ❌ Without: \"I'd estimate you have around 10-15 support tickets...\"\n- ✅ With: \"Zendesk shows 32 tickets, 12 high priority, avg response time 2.3hrs\"\n\n**Examples of what you can build:**\n- ? Calendar → \"What meetings do I have tomorrow? Who's attending?\"\n- ? Email → \"Find emails from Sarah about the Q1 roadmap\"\n- ? Slack → \"What did #product-team discuss today?\"\n- ? Analytics → \"Show me feature adoption for our enterprise tier\"\n- ? Any API → If it has an API, we can probably connect it\n\n**Benefits:**\n- Real data, not AI guessing\n- Guardrails prevent hallucination\n- Live queries, not stale training data\n- Structured tools with validation\n\n**This wizard will:**\n1. Help you describe what you want to connect\n2. Design the integration together\n3. Generate the MCP server code\n4. Integrate it into Amp\n5. Update all documentation so future sessions know how to use it\n\nReady to get started? **What would you like to connect Amp to?**\n\n(Just describe it in plain English — e.g., \"my Google Calendar\", \"Notion database\", \"company CRM\")\n```\n\n### If service hint provided:\n\nSkip education and jump to Phase 1 with the hint as starting context.\n\n---\n\n## Phase 1: Understand the Connection\n\n### Goal: Get clarity on what service and what data\n\nAsk these questions (adapt based on what's already known):\n\n**Question 1: Service identification**\n```\nWhat service or tool do you want to connect?\n\nExamples:\n- A specific app (Google Calendar, Notion, Salesforce)\n- A type of data (my emails, my tasks, my documents)\n- An API you have access to\n\nYour answer:\n```\n\n**Question 2: Authentication**\n```\nHow do you currently access this service?\n\n1. I log in with username\u002Fpassword\n2. I have an API key\n3. It uses OAuth (Google, Microsoft login)\n4. It's a local file or database\n5. Something else\n\nThis helps me understand what authentication we'll need.\n```\n\n**Question 3: Data of interest**\n```\nWhat specific information do you want Amp to access?\n\nBe specific about:\n- What types of data (events, messages, records)\n- What you'd want to read vs. write\n- Any specific fields that matter most\n\nExample: \"I want to see my calendar events - title, time, attendees. Just reading, no need to create events.\"\n```\n\n**Question 4: Use cases**\n```\nHow would you actually use this in practice?\n\nGive me 2-3 example questions or commands you'd want to ask:\n- \"Show me today's meetings\"\n- \"Find emails from [person] about [topic]\"\n- \"What's the status of [account]?\"\n\nThis shapes what tools we'll build.\n```\n\n### After Phase 1, summarize:\n\n```\n**Understood. Here's what we're building:**\n\n? **Service:** [service name]\n? **Auth method:** [auth type]\n? **Data access:** [read\u002Fwrite + what data]\n? **Primary use cases:**\n1. [use case 1]\n2. [use case 2]\n3. [use case 3]\n\nDoes this capture what you want? (yes \u002F let me clarify)\n```\n\n---\n\n## Phase 2: Design the Tools\n\n### Goal: Define the specific MCP tools to build\n\nBased on use cases, propose tool designs:\n\n```\n**Proposed MCP Tools**\n\nBased on your use cases, here's what I suggest building:\n\n| Tool Name | What It Does | Example Usage |\n|-----------|--------------|---------------|\n| `[tool_1]` | [description] | \"[natural language example]\" |\n| `[tool_2]` | [description] | \"[natural language example]\" |\n| `[tool_3]` | [description] | \"[natural language example]\" |\n\n**Input parameters for each:**\n\n### `[tool_1]`\n- `param_1` (required): [description]\n- `param_2` (optional): [description]\n\n### `[tool_2]`\n...\n\n**Questions:**\n1. Do these tools cover your use cases?\n2. Should any tool do more or less?\n3. Are there additional scenarios I missed?\n```\n\n### Iterate until user confirms design\n\nKeep refining based on feedback. Ask focused questions:\n- \"Should [tool] also support [capability]?\"\n- \"What happens if [edge case]?\"\n- \"Do you need to filter by [field]?\"\n\n### Confirm before implementation:\n\n```\n**Final Tool Design**\n\nWe're building an MCP server called `[server-name]` with:\n\n| Tool | Purpose | Inputs |\n|------|---------|--------|\n| [tool] | [purpose] | [inputs summary] |\n\n**Authentication:** [method + what user needs to provide]\n**Configuration:** [any env vars or config needed]\n\nReady to build? (yes \u002F let me adjust)\n```\n\n---\n\n## Phase 3: Implementation\n\n### Goal: Generate the MCP server code\n\n**Step 3.1: Create the server file**\n\nGenerate Python code following the pattern in `core\u002Fmcp\u002Fwork_server.py`:\n\n```python\n#!\u002Fusr\u002Fbin\u002Fenv python3\n\"\"\"\nMCP Server for [Service Name]\n[Brief description of what this server does]\n\nTools:\n- [tool_1]: [description]\n- [tool_2]: [description]\n\"\"\"\n\nimport os\nimport json\nimport logging\nfrom typing import Dict, List, Optional, Any\nfrom datetime import datetime\n\nfrom mcp.server import Server, NotificationOptions\nfrom mcp.server.models import InitializationOptions\nimport mcp.server.stdio\nimport mcp.types as types\n\n# Set up logging\nlogging.basicConfig(level=logging.INFO)\nlogger = logging.getLogger(__name__)\n\n# Configuration from environment\n[RELEVANT_CONFIG_VARS]\n\n# ============================================================================\n# SERVICE CLIENT\n# ============================================================================\n\nclass [ServiceName]Client:\n    \"\"\"Client for interacting with [Service]\"\"\"\n    \n    def __init__(self):\n        [initialization code]\n    \n    [methods for each operation]\n\n# ============================================================================\n# MCP SERVER\n# ============================================================================\n\napp = Server(\"[server-name]-mcp\")\nclient = [ServiceName]Client()\n\n@app.list_tools()\nasync def handle_list_tools() -> list[types.Tool]:\n    \"\"\"List all available tools\"\"\"\n    return [\n        types.Tool(\n            name=\"[tool_name]\",\n            description=\"[tool description]\",\n            inputSchema={\n                \"type\": \"object\",\n                \"properties\": {\n                    [property definitions]\n                },\n                \"required\": [required fields]\n            }\n        ),\n        # ... more tools\n    ]\n\n@app.call_tool()\nasync def handle_call_tool(\n    name: str, arguments: dict | None\n) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:\n    \"\"\"Handle tool calls\"\"\"\n    \n    if name == \"[tool_name]\":\n        [implementation]\n        return [types.TextContent(type=\"text\", text=json.dumps(result, indent=2))]\n    \n    # ... more tool handlers\n    \n    return [types.TextContent(type=\"text\", text=f\"Unknown tool: {name}\")]\n\nasync def _main():\n    \"\"\"Async main entry point\"\"\"\n    logger.info(\"Starting [Service] MCP Server\")\n    \n    async with mcp.server.stdio.stdio_server() as (read_stream, write_stream):\n        await app.run(\n            read_stream,\n            write_stream,\n            InitializationOptions(\n                server_name=\"[server-name]-mcp\",\n                server_version=\"1.0.0\",\n                capabilities=app.get_capabilities(\n                    notification_options=NotificationOptions(),\n                    experimental_capabilities={},\n                ),\n            ),\n        )\n\ndef main():\n    \"\"\"Sync entry point\"\"\"\n    import asyncio\n    asyncio.run(_main())\n\nif __name__ == \"__main__\":\n    main()\n```\n\nSave to: `core\u002Fmcp\u002F[service_name]_server.py`\n\n**Step 3.2: Update requirements**\n\nAdd any new dependencies to `requirements.txt`\n\n**Step 3.3: Create launcher script (if needed)**\n\nCreate `core\u002Fmcp\u002Frun_[service_name].sh`:\n\n```bash\n#!\u002Fbin\u002Fbash\n# Launch [Service] MCP server\ncd \"$(dirname \"$0\")\"\nsource venv\u002Fbin\u002Factivate 2>\u002Fdev\u002Fnull || true\npython [service_name]_server.py\n```\n\nMake executable: `chmod +x run_[service_name].sh`\n\n### Tell user what was created:\n\n```\n**Server Created!** ✅\n\nFiles generated:\n- `core\u002Fmcp\u002F[service_name]_server.py` — The MCP server\n- `requirements.txt` — Updated with dependencies\n\n**Before we integrate, you'll need to:**\n\n[Auth-specific instructions based on Phase 1]\n\nExamples:\n- For API key: \"Add [SERVICE]_API_KEY to your environment or .env file\"\n- For OAuth: \"Run the OAuth setup script: `python core\u002Fmcp\u002Fsetup_[service]_auth.py`\"\n- For local: \"No additional setup needed\"\n\nLet me know when you're ready to integrate.\n```\n\n---\n\n## Phase 4: Integration\n\n### Goal: Connect the MCP server to Amp\n\n**Step 4.1: Update CLAUDE.md**\n\nAdd to the Integration Options section or create new MCP section:\n\n```markdown\n### [Service Name] Integration\n\n**Server:** `core\u002Fmcp\u002F[service_name]_server.py`\n**Purpose:** [what it does]\n\n**Available Tools:**\n\n| Tool | What It Does | Example |\n|------|--------------|---------|\n| `[tool]` | [description] | \"[natural example]\" |\n\n**Configuration Required:**\n- `[ENV_VAR]`: [description]\n\n**Usage examples:**\n- \"[natural language request]\" → uses `[tool]` tool\n- \"[another request]\" → uses `[another_tool]` tool\n```\n\n**Step 4.2: Add MCP Instructions (if not present)**\n\nCheck if CLAUDE.md has mcp_instructions section. If not, add:\n\n```markdown\n\u003Cmcp_instructions>\n### [service-name]-mcp\n\n[Description of the server and when to use it]\n\n**Tools:**\n- `[tool_name]`: [when to use and what it returns]\n\n\u003C\u002Fmcp_instructions>\n```\n\n**Step 4.3: Update System Guide**\n\nAdd to `06-Resources\u002FAmp_System\u002FAmp_System_Guide.md` under Integration Options:\n\n```markdown\n| **[Service]** | [Brief description of capabilities] |\n```\n\nAnd add a new section if significant:\n\n```markdown\n### [Service] MCP Server\n\nServer: `core\u002Fmcp\u002F[service_name]_server.py`\n\n#### Available Tools\n\n| Tool | Purpose |\n|------|---------|\n| `[tool]` | [description] |\n\n#### Usage\n\n[How to use in natural language, what to expect]\n\n#### Configuration\n\n| Variable | Description |\n|----------|-------------|\n| `[ENV_VAR]` | [what it's for] |\n```\n\n---\n\n## Phase 5: Verification\n\n### Goal: Ensure everything is properly connected\n\n**Run verification checklist:**\n\n```\n**Integration Complete!** ?\n\nLet me verify everything is in place:\n\n✅ Server created: `core\u002Fmcp\u002F[service_name]_server.py`\n✅ Dependencies updated: `requirements.txt`\n✅ CLAUDE.md updated with integration docs\n✅ System Guide updated\n\n**To start using it:**\n\n1. Install dependencies (if new ones added):\n   ```\n   pip install -r requirements.txt\n   ```\n\n2. Add your credentials:\n   ```\n   export [ENV_VAR]=\"your-value-here\"\n   ```\n   Or add to your shell config \u002F .env file.\n\n3. Configure Claude Desktop to use the server:\n   Edit `~\u002FLibrary\u002FApplication Support\u002FClaude\u002Fclaude_desktop_config.json`:\n   ```json\n   {\n     \"mcpServers\": {\n       \"[server-name]\": {\n         \"command\": \"python\",\n         \"args\": [\"[full-path]\u002Fcore\u002Fmcp\u002F[service_name]_server.py\"],\n         \"env\": {\n           \"VAULT_PATH\": \"[full-path-to-amp]\"\n         }\n       }\n     }\n   }\n   ```\n\n4. Test it! Try asking:\n   - \"[example natural language query]\"\n\n**Want me to help you test the integration?**\n```\n\n---\n\n## Example Walkthrough\n\n```\nUser: \u002Fcreate-mcp\n\nClaude: [Shows education intro]\n\nUser: I want to connect my Todoist\n\nClaude: Great choice! Let me understand what you need...\n\n[Phase 1 questions]\n\nUser: I want to see my tasks, add new ones, and mark them complete.\n      Example: \"What's on my Todoist today?\" or \"Add 'buy groceries' to Todoist\"\n\nClaude: **Understood. Here's what we're building:**\n\n? **Service:** Todoist\n? **Auth method:** API key (Todoist provides this)\n? **Data access:** Read tasks, create tasks, update task status\n? **Primary use cases:**\n1. \"What's on my Todoist today\u002Fthis week?\"\n2. \"Add [task] to Todoist\"\n3. \"Mark [task] as done in Todoist\"\n\nDoes this capture what you want?\n\nUser: Yes, but also let me filter by project\n\nClaude: Got it! Adding project filtering...\n\n[Phase 2 - Tool design]\n\n**Proposed MCP Tools**\n\n| Tool Name | What It Does |\n|-----------|--------------|\n| `list_tasks` | Get tasks with filters (today, date range, project) |\n| `create_task` | Add a new task to Todoist |\n| `complete_task` | Mark a task as done |\n| `list_projects` | See available projects |\n\n[Continues through phases...]\n```\n\n---\n\n## Behaviors\n\n### Always Do\n- Start with education for new users\n- Confirm understanding before building\n- Generate complete, working code\n- Update ALL documentation (CLAUDE.md, System Guide)\n- Provide clear setup instructions\n- Offer to help test\n\n### Never Do\n- Skip the design phase\n- Generate partial\u002Fplaceholder code\n- Forget to update documentation\n- Assume authentication works without explaining setup\n- Create tools without clear use cases\n\n### If stuck on technical details\n- Search for the service's API documentation\n- Check if an existing Python library handles auth\n- Offer simpler alternatives if complexity is high\n\n---\n\n## Integration Checklist\n\nAfter completion, verify:\n\n- [ ] Server file created in `core\u002Fmcp\u002F`\n- [ ] Requirements.txt updated\n- [ ] CLAUDE.md has integration documentation\n- [ ] System Guide updated with new capabilities\n- [ ] Setup instructions are clear and complete\n- [ ] Example queries provided for testing\n\n### Analytics (Required)\n\n- [ ] Events defined for key tools (e.g., `{tool}_used`)\n- [ ] Added checkbox to `System\u002Fusage_log.md` (Integrations section)\n- [ ] Privacy verified: only tracks that feature was used, not content\n\nSee `.claude\u002Freference\u002Fskill-analytics-checklist.md` for detailed guidance.\n- [ ] User knows how to configure Claude to use the server\n\n---\n\n## Track Usage (Silent)\n\nUpdate `System\u002Fusage_log.md` to mark MCP creation as used.\n\n**Analytics (Silent):**\n\nCall `track_event` with event_name `mcp_created` and properties:\n- (no properties — do NOT include service names)\n\nThis only fires if the user has opted into analytics. 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