FRENES

Maps, places and travel · MCP server

Weekly Weather MCP: MCP server, setup and security

Weekly Weather MCP is an open-source MCP server that lets an AI agent retrieve detailed seven-day weather forecasts for locations around the world. Its repository has 10 stars and its last commit is from January 16, 2026 and it is licensed under MIT.

Score
35/100
Adoption (stars) 10/40
Maintenance 10/30
Framework (licence, registry, official) 15/30
Last commit 9 months ago

What Weekly Weather MCP does

According to its repository: “Detailed seven-day weather forecasts for anywhere in the world.”

An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Weekly Weather MCP is listed under Maps, places and travel, a category of 67 servers in the directory, where it ranks #39 by stars.

Topics declared by the repository: onecallapi, weather.

Installing and connecting Weekly Weather MCP

No package or remote server is declared in the official MCP registry: you install it from source, following the repository README.

Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: Python.

Security: what to check

An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Weekly Weather MCP. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on April 8, 2025, the rossshannon/weekly-weather-mcp repository has 10 stars and 7 forks, with 0 open issues. It has more stars than 26% of the servers in the directory. Last change 9 months ago.

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

LetsFG — Flights & HotelsLetsFG — Flights & Hotels : 2.2K2.2KQGIS MCPQGIS MCP : 1.1K1.1KMCP server airbnbMCP server airbnb : 550550Google Maps MCP ServerGoogle Maps MCP Server : 479479GeoLensGeoLens : 281281Submitmap MCPSubmitmap MCP : 261261Open streetmap MCPOpen streetmap MCP : 230230Gis MCPGis MCP : 198198Weekly Weather MCPWeekly Weather MCP : 1010
GitHub stars of the most followed servers in the category (log scale); Weekly Weather MCP in orange. Checked October 25, 2026.

Verdict

Weekly Weather MCP is still a modest project: read its code and compare it with the alternatives before using it.

Strengths

  • Permissive licence (MIT)

Limitations

  • No commit for 9 months
  • Few visible users
  • Install from source

Frequently asked questions

How do I install Weekly Weather MCP?

No package is declared in the MCP registry: clone the rossshannon/weekly-weather-mcp repository, follow its README, then declare the start command in your client's MCP configuration.

Is Weekly Weather MCP free?

The code is published under the MIT licence and can be used free of charge.

Is Weekly Weather MCP safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by rossshannon on GitHub. Check who maintains it before giving it access.

What are the alternatives to Weekly Weather MCP?

In the same category: GeoLens, LetsFG — Flights & Hotels, Google Maps MCP Server, and Cesium MCP. GeoLens and LetsFG — Flights & Hotels score higher on our grid.

Related articles

Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score