Tern EV-Charging Analytics for LangChain
io.github.useternai/usetern
EV-charging site analytics: utilization, demand, peak saturation and corridor benchmarks.
client:LangChain
transport:streamable-http
tools:26
Install Tern EV-Charging Analytics in LangChain
pip install langchain-mcp-adapters
from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient({
"usetern": {
"transport": "streamable_http",
"url": "https://tern-mcp-537572042041.europe-west4.run.app/mcp",
}
})
tools = await client.get_tools()
get_tools() returns the server's tools as LangChain tools, ready for an agent. LangChain docs
What LangChain can do once it is connected
- search_charging_stations
- nearby_charging_stations
- list_evses
- aggregate_charging_utilization
- aggregate_evse_utilization
- area_benchmark
- avg_session_minutes
- busy_evse_hours
- corridor_benchmark
- corridor_comparison
- daily_spike
- day_vs_similar
- demand_share_multiple
- estate_coverage
- estate_monthly_series
- hourly_spike
- monthly_sessions_per_stall_day
- peak_hour_co_saturation
- poi_context
- rank_gap
- road_context
- sessions_per_stall_day
- site_profile
- site_ranking