swarm-mcp

swarm-mcp

An MCP server that provides access to Foursquare Swarm check-in data, enabling AI assistants to query check-in history, stats, top venues, and venue details.

Category
访问服务器

README

Swarm MCP Server

An MCP (Model Context Protocol) server that provides access to your Foursquare Swarm check-in data. Use it with Claude Desktop, Claude Code, or any MCP-compatible client to analyze your check-in history.

Features

Tool Description
get_checkins Get paginated check-in history
get_checkins_by_date_range Get check-ins within a specific date range
get_recent_checkins Get check-ins from the past X days
get_checkin_details Get details about a specific check-in
get_venue_details Get venue info: ratings, hours, tips, photos
get_all_checkins Retrieve your entire check-in history
get_checkin_stats Get statistics (total count, date range, averages)
get_categories List all unique categories in your history with counts
get_top_venues Get your most visited venues with filters
search_checkins Search with filters: query, category, city, state, country, date range
get_server_info Get server metadata, data sources, and tool costs

All responses include a _meta block with transparency info (completeness, API calls made, data scope) to help AI models make informed decisions about expensive operations.

Tool Costs

Tool Cost Notes
get_checkins Low Single paginated request
get_checkins_by_date_range Low Single request with date filters
get_recent_checkins Low Single request with time filter
get_checkin_details Low Single check-in lookup
get_venue_details Low Single venue lookup
get_checkin_stats Low 2 API calls (newest + oldest)
get_categories High Scans history to discover unique categories
get_top_venues High Scans history to aggregate venue visits
get_server_info None Local introspection only
get_all_checkins High 1 API call per 250 check-ins
search_checkins High Client-side filtering; scans up to 5000 items

Example _meta Response

Every tool response includes metadata like this:

{
  "_meta": {
    "is_complete": true,
    "returned_count": 50,
    "total_available": 1847,
    "limit_applied": 50,
    "api_calls_made": 1,
    "data_source": "foursquare_swarm_api",
    "data_scope": "authenticated_user_checkins"
  },
  "checkins": [...]
}

Installation

Using uvx (recommended)

uvx swarm-mcp

Using pip

pip install swarm-mcp

Setup

1. Get Your Foursquare Access Token

You'll need a Foursquare OAuth2 access token:

  1. Go to Foursquare Developer Apps
  2. Create a new app (or use an existing one)
  3. Note your Client ID and Client Secret
  4. Generate an access token using the OAuth2 flow, or use the API Explorer to get a token quickly

Security: Treat FOURSQUARE_TOKEN like a password—don't commit it, paste it in issues, or share screenshots with it visible.

2. Configure Your MCP Client

Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "swarm": {
      "command": "uvx",
      "args": ["swarm-mcp"],
      "env": {
        "FOURSQUARE_TOKEN": "your-access-token-here"
      }
    }
  }
}

Claude Code

claude mcp add swarm uvx swarm-mcp -e FOURSQUARE_TOKEN=your-access-token-here

Or add manually to your config:

{
  "Swarm": {
    "command": "uvx",
    "args": ["swarm-mcp"],
    "env": {
      "FOURSQUARE_TOKEN": "your-access-token-here"
    }
  }
}

Usage Examples

Once configured, you can ask Claude things like:

  • "Show me my recent Swarm check-ins"
  • "How many times have I checked into coffee shops this year?"
  • "What are my top 10 most visited coffee shops?"
  • "Show me all my check-ins in California"
  • "What are my check-in stats?"
  • "Get details about [venue name]" (ratings, hours, tips)
  • "What are the ratings for my favorite restaurants?"

Example Output

📊 SWARM CHECK-IN STATS
=============================================
Total check-ins:      12,456
Years active:         10.2 years
Days active:          3,726
Avg check-ins/day:    3.34

📅 First check-in: March 15, 2014 at Coffee Shop (NYC)
📍 Most recent: Today at Office (San Francisco)

Development

# Clone the repo
git clone https://github.com/alexpriest/swarm-mcp.git
cd swarm-mcp

# Install in development mode
pip install -e .

# Run the server
FOURSQUARE_TOKEN=your-token swarm-mcp

API Reference

This server uses the Foursquare API v2:

License

MIT License - see LICENSE for details.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选
mcp-server-qdrant

mcp-server-qdrant

这个仓库展示了如何为向量搜索引擎 Qdrant 创建一个 MCP (Managed Control Plane) 服务器的示例。

官方
精选
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选