# NYC Cycling & Bike Infrastructure AI Agent Connect

> NYC Cycling & Bike Infrastructure MCP gives your AI agent direct access to the city's cycling network. You can query nearly 30,000 bike route segments, locate 38,000 parking spots, and pull live traffic counts from street sensors. It's a keyless way to map protected lanes, find secure corrals, and check real-time congestion on bridges and boulevards.

## Overview
- **Category:** government-public-data
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_3P46RSzw0PDTHAxf04vdii8m7mlX1Du1VtzGnGRA/ai-agent-connect
- **Tags:** new-york, nyc, cycling, bike-lanes, greenways, bike-parking, corrals, traffic-counts

## Description

You can now give your AI client a complete map of New York City's cycling landscape. Instead of digging through messy city databases, you just ask your agent for the specifics. You can trace protected lanes street by street to find the safest routes or locate one of the 38,000 bike racks and 912 secure corrals when you need to park for a few hours. If you want to know if a specific corridor is packed, you can pull live 15-minute interval counts from street sensors to see exactly how many cyclists, pedestrians, or scooters are passing through right now. This MCP handles the heavy lifting of querying NYC Open Data, letting you focus on planning your route or analyzing commuter patterns without needing an API key.

## Tools

### bike_direction_split
This tool compares inbound and outbound traffic volumes for a specific travel mode. Use it to see if a bridge or corridor has a heavy commuter bias in one direction.

### count_bike_lanes
This tool returns a fast count of NYC bike route segments that match your specific filters. It's useful for quickly gauging the scale of a route or street before pulling more detailed data.

### list_bike_corrals
This tool identifies the 912 secure and community bike corrals across the city. Use it when you need a more reliable parking option than a standard chainable rack.

### list_bike_lanes
This tool provides details on approximately 29,700 bike route segments, including facility types like Protected or Shared. You can filter by borough or street to trace the network for trip planning.

### search_bike_flows
This tool pulls raw 15-minute interval counts from live traffic sensors. It provides the specific volume of bikes, pedestrians, or scooters at a given street or intersection.

### search_bike_parking
This tool searches through 38,000 bike racks and corrals citywide. It returns addresses and street locations to help you find a place to lock up near your destination.

### top_bike_greenways
This tool ranks the named greenways in NYC by their segment count. Use it to identify the primary long-distance cycling corridors in the city.

### top_bike_sensors
This tool identifies the busiest bike, pedestrian, or scooter sensors based on total volume. It helps you find the highest traffic areas within a specific lookback window.

## Prompt Examples

**Prompt:** 
```
Where are the protected bike lanes on First Avenue in Manhattan?
```

**Response:** 
```
The protected segments on 1 AV in Manhattan include the stretch between the cross streets provided in the route data.
```

**Prompt:** 
```
How busy is the bike traffic on the Williamsburg Bridge right now?
```

**Response:** 
```
Current sensor data shows the volume of cyclists passing through the Williamsburg Bridge bike path for the most recent 15-minute intervals.
```

**Prompt:** 
```
Where can I leave a bike for hours in Manhattan?
```

**Response:** 
```
You can use the secure community corrals located at several addresses in Manhattan, such as those near major transit hubs.
```

## Capabilities

### Route Mapping
Your agent can trace protected and conventional bike lanes street by street.

### Parking Discovery
The AI can find specific chainable racks or secure corrals near any destination.

### Live Traffic Monitoring
You can check real-time sensor counts for bikes, pedestrians, and scooters.

### Commuter Analysis
The tool calculates direction splits to show inbound versus outbound traffic trends.

### Greenway Identification
Your agent can identify and rank the major greenways used for long-distance riding.

## Use Cases

### Safe Commuting
Ask your agent to find a route using only protected bike lanes to avoid heavy car traffic.

### Secure Parking
Locate a secure community corral when you need to leave your bike unattended for a long period.

### Traffic Assessment
Check how busy a specific bridge or boulevard is before you head out for a ride.

### Infrastructure Research
Query the total number of bike segments or greenway lengths for urban studies.

## Benefits

- Access live sensor data without managing your own API keys.
- Find secure parking locations instantly through natural language queries.
- Identify protected cycling infrastructure to plan safer routes.
- Analyze real-time traffic volumes for bikes and pedestrians.

## How It Works

Connecting to this MCP gives your AI client immediate access to NYC's cycling datasets.

1. Connect your preferred MCP-compatible client to Vinkius.
2. Ask your AI agent a question about NYC bike lanes, parking, or traffic.
3. The agent calls the specific tool needed to query the NYC Open Data.
4. The agent receives the raw data and translates it into a clear answer for you.

## Frequently Asked Questions

**Do I need an API key to use this NYC cycling data?**
No. Vinkius hosts the MCP, so you get keyless access to the data through your AI client.

**How recent is the traffic sensor data?**
The sensor readings are live and include 15-minute interval counts collected up to today.

**Can I find secure parking instead of just regular bike racks?**
Yes. You can specifically search for the 912 secure and community bike corrals using the list_bike_corrals tool.

**Which AI clients can I use with this MCP?**
You can use any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

**How do I search for a specific street?**
When asking your agent to search, ensure the street name matches the casing used in the results, as the data uses specific uppercase and mixed-case formats.

**Do I need an API key?**
No. NYC Open Data serves all public datasets anonymously over its SODA API (data.cityofnewyork.us). This MCP defines no credentials and needs nothing configured.

**Do the text filters ignore case or match partial values?**
No. The NYC data platform only supports exact-match filters, and each table stores its values differently: the bike-route table stores the boro as the numeric code 1-5 and the street in UPPERCASE ("1 AV" — the tool auto-uppercases the street input); the bike-parking table stores the boro in title case ("Brooklyn", "Staten Island") and mixes street casings (e.g. "BROADWAY" and "Broadway" — pass the street as it appears in a result row). Facility classifications are stored as "Protected", "Conventional", "Shared", "Signed Route", "Wide Parking Lane", "Sidewalk" or "Curbside", and the greenway names are a short set ("Manhattan Waterfront", "Jamaica Bay", "Brooklyn Waterfront", ...). Use list_bike_lanes or search_bike_parking with no filters to see the exact stored values before filtering.

**What do the direction codes on bike routes mean?**
The route segments carry a short direction code: "L" for left-side/one-way, "R" for right-side/one-way and "2" for two-way operation. Use it to read which way a one-way street's bike lane flows.

**How do sensor ids map to streets?**
top_bike_sensors returns numeric sensor ids. Call search_bike_flows with that sensor id: the flowname field carries the street context, e.g. "87th ST. and Columbus IN" or "Manhattan Bridge Display Bike Counter Cyclist IN". Only 15-minute interval readings are returned (hourly summary rows are excluded), and the counts are live, collected up to today.