mcpField
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Wishfinity +w

Wishfinity +w

Local
github.com/wishfinityProductivity1Updated 34w ago

About Wishfinity +w

Wishfinity +w is an MCP server for saving product links to a user's Wishfinity wishlist from AI shopping and gift conversations. It returns a link the user clicks to save an item, requires no API key, and supports local stdio and remote HTTP transports.

Key features

  1. 01Add product links to a wishlist
  2. 02Return a save link for user action
  3. 03Support stdio and HTTP transports
  4. 04Provide prompts and resources

Use cases

  1. 01Save recommended products for later purchase
  2. 02Collect gift candidates in a wishlist
  3. 03Bookmark items when postponing a purchase
  4. 04Integrate wishlist actions into AI applications

MCP support

The MCP server provides the add_to_wishlist tool, which accepts a product URL and returns a Wishfinity link that the user clicks to save the item. It also provides MCP prompts and resources, with stdio and HTTP transports.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"wishfinity-mcp-plusw": {
"command": "npx",
"args": [
"-y",
"wishfinity-mcp-plusw"
]
}
}
}
Run commandnpx -y wishfinity-mcp-plusw

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmwishfinity-mcp-plusw1.2.2

Tools

1

Saved tool list · updated 3w ago

ParameterTypeRequiredDescription
urlstringYesThe product page URL to save to the wishlist

Details

From the project README

+W MCP Server (Wishfinity)

+W is a universal "save for later" action for commerce. This MCP server lets AI assistants save any product URL to a user's Wishfinity wishlist with one click.

Works with Claude, ChatGPT, Gemini, LangChain, OpenAI Agents SDK, and any MCP-compatible client.

npm version License: MIT

What it does

When an AI recommends a product, it can offer +W Add to Wishlist. The user clicks the link, and the product is saved to their Wishfinity account — ready for later purchase or gifting.

User: "Find me a good espresso machine under $200"

AI: Here are 3 options...
    [+W Add to Wishlist] [View on Amazon]

Zero-dependency option: /add-wish

Don't need the full MCP server? The /add-wish skill teaches any AI agent the +W pattern using just a URL — no npm, no server, no setup:

https://wishfinity.com/add?url={any_product_url}

→ View the /add-wish skill file

Works with any AI platform. The MCP server below adds richer tool integration, but /add-wish is all you need to get started.

Quick start

Option 1: Local installation (stdio transport)

Best for Claude Desktop, ChatGPT Desktop, Cursor, VS Code, and local development.

npm install wishfinity-mcp-plusw

Add to your MCP client configuration:

{
  "mcpServers": {
    "wishfinity": {
      "command": "npx",
      "args": ["wishfinity-mcp-plusw"]
    }
  }
}
Option 2: Remote endpoint (HTTP transport)

Best for server-side agents, LangChain production deployments, and hosted AI applications.

https://wishfinity-mcp-plusw.wishfinity.workers.dev/mcp

Platform Setup Guides

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "wishfinity": {
      "command": "npx",
      "args": ["wishfinity-mcp-plusw"]
    }
  }
}
ChatGPT Desktop

When MCP support is available, add to your ChatGPT MCP configuration:

{
  "mcpServers": {
    "wishfinity": {
      "command": "npx",
      "args": ["wishfinity-mcp-plusw"]
    }
  }
}
Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "wishfinity": {
      "command": "npx",
      "args": ["wishfinity-mcp-plusw"]
    }
  }
}
LangChain
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent

async def main():
    client = MultiServerMCPClient({
        "wishfinity": {
            "command": "npx",
            "args": ["wishfinity-mcp-plusw"],
            "transport": "stdio",
        }
    })

    tools = await client.get_tools()
    agent = create_agent("openai:gpt-4", tools)

    result = await agent.ainvoke({
        "messages": [{"role": "user", "content": "Find me a coffee maker and save it to my wishlist"}]
    })

For production (HTTP transport):

client = MultiServerMCPClient({
    "wishfinity": {
        "url": "https://wishfinity-mcp-plusw.wishfinity.workers.dev/mcp",
        "transport": "streamable_http",
    }
})
OpenAI Agents SDK
from agents import Agent, Runner
from agents.mcp import MCPServerStdio

async def main():
    async with MCPServerStdio(
        name="wishfinity",
        params={
            "command": "npx",
            "args": ["wishfinity-mcp-plusw"],
        },
    ) as server:
        agent = Agent(
            name="Shopping Assistant",
            instructions="Help users find products and save them to wishlists.",
            mcp_servers=[server],
        )

        result = await Runner.run(agent, "Find a good gift for a coffee lover and save it")
        print(result.final_output)
Hugging Face Agents
from huggingface_hub import Agent

agent = Agent(
    model="meta-llama/Llama-3.1-70B-Instruct",
    mcp_servers=[{
        "command": "npx",
        "args": ["wishfinity-mcp-plusw"]
    }]
)

response = agent.run("Find me running shoes under $150 and save to wishlist")

How it works

  1. AI calls the add_to_wishlist tool with a product URL
  2. MCP server returns a Wishfinity link: https://wishfinity.com/add?url=...
  3. User clicks the link → logs in (first time only) → product is saved
  4. User can organize, share, or purchase later

No API keys required. Authentication happens on Wishfinity's website when the user clicks the link.


Tool: add_to_wishlist

Input
ParameterTypeRequiredDescription
urlstringYesProduct page URL
Output
FieldTypeDescription
action_urlstringWishfinity link to open in browser
requires_user_actionbooleanAlways true (user must click)
display_textstringSuggested button label
Example
// Input
{ "url": "https://amazon.com/dp/B0EXAMPLE" }

// Output
{
  "action_url": "https://wishfinity.com/add?url=https%3A%2F%2Famazon.com%2Fdp%2FB0EXAMPLE",
  "requires_user_action": true,
  "display_text": "Open to add to Wishfinity"
}

When to offer +W

AI clients should offer +W when:

  • Explicit requests: "save for later," "add to wishlist," "bookmark this"
  • After recommending products: Proactively offer to save shown items
  • Indecision moments: "maybe later," "too expensive right now," "need to think about it"
  • Gift context: "for my mom," "birthday gift," "perfect for my friend"

See aliases.json for the full list of trigger phrases.


Transports

TransportUse CaseEndpoint
stdioLocal clients (Claude Desktop, Cursor, etc.)npx wishfinity-mcp-plusw
HTTPRemote/server-side agentshttps://wishfinity-mcp-plusw.wishfinity.workers.dev/mcp

Button kit

The /button-kit folder contains optional UI assets (SVG icon, HTML/CSS snippets) if you want a consistent +W button appearance.

CDN URLs:

  • Small: https://cdn.jsdelivr.net/npm/wishfinity-mcp-plusw@latest/button-kit/Wishfinity-Button-Small.svg
  • Medium: https://cdn.jsdelivr.net/npm/wishfinity-mcp-plusw@latest/button-kit/Wishfinity-Button-Medium.svg
  • Large: https://cdn.jsdelivr.net/npm/wishfinity-mcp-plusw@latest/button-kit/Wishfinity-Button-Large.svg

Documentation


Links


Changelog

v1.2.2 (December 24, 2025)

Critical Fix: npx execution for all developers

  • Fixed main module detection to work with npx symlinks
  • Resolves crash when running npx wishfinity-mcp-plusw
  • Package now works flawlessly for all npm installations
v1.2.1 (December 24, 2025)

Critical Fix: MCP SDK compatibility

  • Updated @modelcontextprotocol/sdk dependency to ^1.25.0
  • Resolves server disconnection with SDK 1.25.1+
  • Compatible with latest MCP SDK versions
v1.2.0 (December 23, 2025)
  • Added MCP prompts: save_for_later, shopping_assistant, gift_ideas
  • Added MCP resources: wishfinity://guide, wishfinity://triggers
  • Enhanced integration capabilities for AI assistants

License

MIT

Comments

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