mcpField
I
instafan

instafan

Remote
instafan.appMaps & Travel0Updated 8w ago

About instafan

instafan is an MCP server for planning trips with friends, using live place data, climate normals, and official safety advisories to support destination choice and daily itineraries. It provides destination briefs, real rated places, and photos, and can be connected without installation or authentication.

Key features

  1. 01Suggest destinations from a travel mood
  2. 02Provide weather and official safety briefs
  3. 03Find real rated places and photos
  4. 04Build day-by-day itineraries
  5. 05Return spot photos with attribution

Use cases

  1. 01Filter destinations by season and preferences
  2. 02Check weather and safety before a trip
  3. 03Find popular places with photos
  4. 04Plan a schedule for a group trip

MCP support

The remote MCP server uses Streamable HTTP at https://instafan.app/mcp and exposes tools for destination discovery, briefs, place searches, itinerary generation, and photos.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://instafan.app/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

5
ParameterTypeRequiredDescription
moodstringYesThe trip mood or constraints, in plain words

Details

From the project README

Instafan MCP Server

Let AI agents plan real trips — where to go for a mood, what a destination is like right now, its strongest Google-rated places with photos, and a day-by-day plan — using Instafan's live data (Google Places, climate normals, official safety advisories).

Hosted, no install, no auth. Streamable-HTTP endpoint:

https://instafan.app/mcp

Tools

ToolWhat it doesInputs
find_destinationsA trip mood or constraint set ("somewhere warm in November, food-first") → 3–5 destination suggestions with the why.mood (required)
destination_briefOne destination: the story, typical weather this month, official safety verdict, a postcard photo link.destination (required)
top_spotsThe strongest real Google-rated places — top attractions by default, or a specific ask like "rooftop bars" — with photo links. Never invented.destination (required), query
build_itineraryA day-by-day plan built from the destination's strongest places.destination, days (both required)
spot_photosUp to two real photos of one spot, embedded inline as MCP image blocks plus direct links, credited to their Google Maps authors.destination (required), spot

Connect

ChatGPT → Settings → Apps & Connectors → enable Developer mode → Create → URL: https://instafan.app/mcp, auth: none.

Claude Desktop / Claude.ai → Settings → Connectors → Add custom connector → URL: https://instafan.app/mcp

Claude Code:

claude mcp add instafan --transport http https://instafan.app/mcp

Cursor / other MCP clients — add a remote (streamable-http) server pointing at the URL above. One-click: see https://instafan.app/connect/

Test with curl:

curl -s -X POST https://instafan.app/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

Example

"Build me a Lisbon trip for my wife and I in the best weather."

The agent calls destination_brief → learns Lisbon is 18–26°C with ~4 rainy days right now and officially rated relaxed; top_spots → real rated places with photos; spot_photos → Belém Tower, inline; build_itinerary → a day-by-day plan. Every answer links back into instafan.app, where the trip becomes a group decision — immerse in 3D, save spots, let the group vote.

About

Built by Instafan — plan trips with friends. https://instafan.app

License

MIT

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.