"How to manage GitHub projects" matching MCP servers:

MCP server for sthan.io - US address verification, parsing, autocomplete, forward/reverse geocoding, and IP geolocation. 8 tools, TypeScript, stdio transport. Free tier, no credit card required.

Thirteen read-only Google Maps Platform tools for an agent: where a place is, what is around it, how long it takes to get there, and what the conditions are when it arrives.

MCP server for spatial queries via the Terranode Geospatial API, enabling AI agents to perform point-in-polygon lookups, nearest feature search, distance calculations, and spatial joins.

A local-first MCP server for tracking beer releases on Vinmonopolet, enabling users to search new and upcoming beers, check store stock, find nearby stores, and manage watchlists.

MCP server for Starbucks — let AI agents search the menu, customize drinks, find stores, place mobile pickup orders, and manage Starbucks Rewards.

Enables AI agents to manage cab bookings, estimate fares, and dispatch drivers with a 2-tier priority algorithm for hotel guests, providing 18 MCP tools for driver management, dispatch, and ride lifecycle.

Tracks how long you've been indoors, nags you to touch grass, detects frustration, and recommends nearby parks with live weather.

The Stadia Maps MCP server provides AI assistants with access to Stadia Maps APIs for location services, geocoding, routing, and mapping capabilities.

Enables AI clients to search trips, find locations, and manage bookings through the Flowteller backend.

Enables querying an OwnTracks Recorder for current and historical location data, including addresses, stays, distances, devices, and status, through read-only MCP tools. It supports natural-language questions about where someone is or was and how far they are from home.

MCP server for the Stream.estate French real estate API. Search properties, get market statistics, manage saved searches with webhook notifications.

Provides Naver Map API functions (geocoding, reverse geocoding, directions, static map, and usage queries) as MCP tools for use in Claude Desktop, VS Code, and other MCP clients.

Enables AI agents to autonomously discover, stream, and compute satellite analytics from free government Earth-observation catalogs such as Sentinel-2, Landsat, and Copernicus DEM, with zero API keys or configuration. It supports place-name geocoding, STAC scene search, cloud-native COG streaming for spectral indices, elevation profiles, SAR flood detection, and sandboxed custom geospatial scripts.

Enables any MCP client to calculate how many calories a user has earned by walking to a destination, then shows which nearby restaurants and dishes fit within that remaining budget. Blends official McDonald's nutrition data with estimated Chinese-restaurant nutrition values and real walking distances, exposing a walk allowance, nearby food lookup, eatability check, and concept explanation as tools.

Enables AI agents to autonomously discover, stream, and compute satellite analytics from free government Earth observation archives. Provides tools for STAC search, spectral indices, elevation profiles, SAR water detection, and sandboxed geospatial scripting.

Enables AI agents to query orders, manage routes, track drivers, and analyze delivery performance on the FleetSync last-mile delivery platform through natural language.

Connect QGIS to Claude AI through the Model Context Protocol (MCP), enabling Claude to directly control QGIS — manage layers, edit features, run processing algorithms, render maps, and more.

Enables Large Language Models to interact with the ILP Drone Delivery System to plan deliveries, check drone availability, and generate route visualizations. It allows users to manage logistics tasks like capacity planning and temperature requirement matching through natural language.

MCP server that provides Korean weather information using grid coordinates and the Korea Meteorological Administration API, allowing users to query current weather conditions and forecasts for specific locations in Korea.

A Python MCP server for discovering and analyzing Sentinel-2 L2A imagery, enabling AI agents to search scenes, check quality, and compute spectral indices like NDVI, NDWI, and NBR from remote COG windows.