# London Cycling and Active Travel AI Agent Connect > London Cycling & Active Travel: Modal Share & Hires provides direct access to official London open-data. Your AI client can pull walking and cycling trip shares by local authority from 2010/11 and 2017/18 surveys, or query TFL's daily bicycle-hire counts. It turns raw mobility data into immediate answers for researchers and planners. ## Overview - **Category:** government-public-data - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_uzxKGGAkx3XKYDRXUYg3slCwa2RKOYvOPSLj26AK/ai-agent-connect - **Tags:** london, united-kingdom, cycling, active-travel, walking, bicycle-hires, tfl, keyless ## Description You can pull official London active-travel datasets directly into your AI client. This MCP connects you to the London open-data platform to analyze how people move through the city. You can compare walking and cycling trip shares across different boroughs using survey data from 2010/11 and 2017/18. If you need to track bike-share trends, you can access TFL's daily bicycle-hire counts, including annual totals and specific peak usage days. The data handles the heavy lifting of converting Excel serial years into readable financial year labels, so you can focus on the analysis. Whether you are looking at high-frequency trips or annual hire volumes, your agent can filter by local authority, date ranges, or specific frequency levels. ## Tools ### active_travel_lookup This tool retrieves walking and cycling time series for a single local authority. It returns the specific shares across the survey years for the requested area. ### active_travel_overview This tool combines both datasets into one call. It provides 2017/18 authority averages alongside hire totals and peak usage days. ### active_travel_ranking This tool ranks local authorities by their cycling rates. It excludes aggregate areas like Inner London to focus on individual borough comparisons. ### active_travel_rates This tool provides GLA walking and cycling rates for the 33 London boroughs and aggregate areas. You can filter by specific local authority, year, or trip frequency. ### bicycle_hires_by_year This tool provides annual Santander Cycles hire totals from 2010 to the most recent data. Each year includes the total count and the busiest day recorded. ### bicycle_hires_daily This tool pulls daily Santander Cycles totals for London. You can use ISO date bounds to narrow down specific timeframes. ## Prompt Examples **Prompt:** ``` What share of Newham trips are by bicycle in 2017/18? ``` **Response:** ``` In the 2017/18 survey, the cycling share for Newham at the 5x per week frequency is [data value]. ``` **Prompt:** ``` Which day had the most bicycle hires? ``` **Response:** ``` Based on the annual hire totals, the busiest day recorded was [date]. ``` **Prompt:** ``` Compare cycling uptake across London boroughs. ``` **Response:** ``` The highest cycling rates are in [Borough A] and [Borough B], while the lowest are in [Borough C] and [Borough D] based on the 2017/18 5x-per-week data. ``` ## Capabilities ### Borough Comparisons Your agent can rank and compare cycling uptake across all 33 London boroughs. ### Time Series Analysis You can pull walking and cycling trends for specific authorities over multiple survey years. ### Bike-Hire Tracking Your client can query daily or annual Santander Cycles hire volumes. ### Peak Demand Identification The agent can identify the busiest days for bicycle hires within any given year. ### Data Aggregation You can request a combined overview of active travel rates and hire totals in a single request. ## Use Cases ### Borough Benchmarking Compare how different London authorities perform in terms of cycling rates. ### Hire Demand Analysis Identify seasonal peaks or the busiest days for Santander Cycles hires. ### Trend Monitoring Track the change in walking and cycling shares between the 2010/11 and 2017/18 surveys. ### Rapid Reporting Generate headline numbers for active travel and bike hires using the overview tool. ## Benefits - Access official London open-data without manual file handling. - Convert Excel-formatted survey years into usable financial year labels automatically. - Query specific trip frequencies like 5x, 20x, or 40x per week. - Get daily hire counts using standard ISO date filters. ## How It Works Connect your client to Vinkius and start querying London mobility data immediately. 1. Connect your MCP-compatible client to Vinkius. 2. Ask your agent to find specific cycling or walking data for a London borough. 3. The agent calls the relevant tool, such as active_travel_lookup or bicycle_hires_daily. 4. The MCP processes the request and returns the data directly to your chat interface. ## Frequently Asked Questions **What years of active travel data are available?** The MCP provides walking and cycling survey data for the 2010/11 and 2017/18 periods. **How do I filter bicycle hire data by date?** You can use the bicycle_hires_daily tool with ISO formatted dates (YYYY-MM-DD) to set your search range. **Does this include Santander Cycles data?** Yes, the bicycle hire tools provide data for Santander Cycles (formerly known as Cycle Hire). **Can I see which borough has the highest cycling rate?** Yes, use the active_travel_ranking tool to see the top and bottom performing local authorities. **Is the data from official sources?** Yes, all data is pulled from the London open-data platform (data.london.gov.uk). **Do I need an API key?** No. data.london.gov.uk publishes every dataset as an anonymous file download (CSV or Excel). This MCP defines no credentials and needs nothing configured. **What do the 5x / 20x / 40x per week frequencies mean?** The survey asks respondents how many times per week they walk or cycle. 5x-per-week is the everyday-use slice and the default for the ranking and overview tools; 20x and 40x are the heavier-use slices. Pick the frequency you are comparing. **Which hire scheme is in the daily series?** The TFL daily counts come from the city's Sycamore (dockless) hire scheme: each row is one calendar day and the hires recorded that day. Per-year totals and the busiest day come from aggregating those rows. **Why are London, Inner London and England out of the ranking?** The ranking compares local authorities against each other; the city-wide and England rows are aggregates, not an authority, so they are excluded by default. Use active_travel_lookup to read those aggregate rows directly.