Skip to main content
Glama
RimeetMavani

Weather MCP Server

by RimeetMavani
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Weather MCP Server

A Model Context Protocol (MCP) server built with fastmcp that exposes exactly 5 weather tools from one API provider (Open-Meteo) — each tool calls a different endpoint on that provider.

Includes a Groq-powered LLM agent and a browser inbox UI. You ask a weather question in plain English; the LLM picks the right Open-Meteo endpoint tool, calls it, and returns an HTML answer. The UI shows which MCP tool was actually called for each query.

Architecture Diagram

flowchart LR
    classDef browser fill:#e0f2fe,stroke:#0284c7,color:#0f172a,stroke-width:1.5px;
    classDef agent fill:#ede9fe,stroke:#7c3aed,color:#0f172a,stroke-width:1.5px;
    classDef mcp fill:#dcfce7,stroke:#16a34a,color:#0f172a,stroke-width:1.5px;
    classDef api fill:#fef3c7,stroke:#d97706,color:#0f172a,stroke-width:1.5px;
    classDef store fill:#f8fafc,stroke:#64748b,color:#0f172a,stroke-width:1px;

    subgraph Browser["Browser UI - index.html :8080"]
        Q["User asks weather question"]:::browser
        H["GET /health"]:::browser
        C["POST /chat { question }"]:::browser
        R["Render tool_used + HTML answer"]:::browser
    end

    subgraph Agent["Groq Agent - agent.py :8001"]
        A1["FastAPI routes"]:::agent
        A2["MCP SSE client"]:::agent
        A3["Groq call #1<br/>pick best tool + extract city"]:::agent
        A4["Groq call #2<br/>format final HTML answer"]:::agent
    end

    subgraph MCP["Weather MCP Server - server.py :8000"]
        M0["SSE endpoint /sse"]:::mcp
        M1["open_meteo_geocode"]:::mcp
        M2["open_meteo_current"]:::mcp
        M3["open_meteo_forecast"]:::mcp
        M4["open_meteo_air_quality"]:::mcp
        M5["open_meteo_historical"]:::mcp
    end

    subgraph OpenMeteo["Open-Meteo provider"]
        E1["/v1/search"]:::api
        E2["/v1/forecast<br/>current weather"]:::api
        E3["/v1/forecast<br/>5-day forecast"]:::api
        E4["/v1/air-quality"]:::api
        E5["/v1/archive"]:::api
    end

    K[".env<br/>GROQ_API_KEY<br/>MCP_SSE_URL"]:::store

    Q --> C
    H --> A1
    C --> A1
    A1 --> A2
    A1 --> A3
    A3 -->|"tool choice + city"| A2
    A2 -->|"list_tools() + call_tool()"| M0
    M0 --> M1
    M0 --> M2
    M0 --> M3
    M0 --> M4
    M0 --> M5
    M1 --> E1
    M2 --> E2
    M3 --> E3
    M4 --> E4
    M5 --> E5
    M0 -->|"HTML tool result"| A4
    A4 -->|"tool_used + html"| R
    K --> A1

Related MCP server: Weather MCP

Query Flow

sequenceDiagram
    autonumber
    participant U as Browser UI
    participant AG as agent.py
    participant G as Groq
    participant M as server.py
    participant O as Open-Meteo

    U->>AG: GET /health
    AG->>M: list_tools() over SSE
    M-->>AG: 5 available open_meteo_* tools
    AG-->>U: agent ok, MCP status, Groq configured

    U->>AG: POST /chat {question}
    AG->>M: list_tools() over SSE
    M-->>AG: tool schemas
    AG->>G: Question + tool schemas
    G-->>AG: Selected tool + city args
    AG->>M: call_tool(tool_name, {city})
    M->>O: HTTP GET to chosen endpoint
    O-->>M: live JSON weather data
    M-->>AG: HTML tool result
    AG->>G: User question + tool name + tool HTML
    G-->>AG: final HTML answer
    AG-->>U: { tool_used, html }
    U->>U: Show tool bar and answer card

The 5 Tools — One Provider, Five Endpoints

#

MCP Tool

Open-Meteo Endpoint

What it returns

1

open_meteo_geocode

geocoding-api.open-meteo.com/v1/search

Coordinates, timezone, region

2

open_meteo_current

api.open-meteo.com/v1/forecast

Current temp, humidity, wind, conditions

3

open_meteo_forecast

api.open-meteo.com/v1/forecast

5-day daily high/low, rain

4

open_meteo_air_quality

air-quality-api.open-meteo.com/v1/air-quality

AQI, PM2.5, PM10, ozone

5

open_meteo_historical

archive-api.open-meteo.com/v1/archive

Yesterday's min/max temp, conditions

All 5 tools use Open-Meteo only — free, no weather API key required.

API Keys

Key

Required for

Sign up

GROQ_API_KEY

LLM inbox UI (agent.py)

https://console.groq.com/keys (free tier)

Weather tools need no API key. Only Groq is required for the inbox UI.

copy .env.example .env
# Edit .env — add GROQ_API_KEY

Quick Start

1. Install dependencies

git clone https://github.com/RimeetMavani/weather-mcp--build.git
cd weather-mcp--build
pip install -r requirements.txt

2. Configure Groq API key

copy .env.example .env
# Edit .env — add GROQ_API_KEY (required for LLM inbox)

3. Start the MCP server (SSE on port 8000)

python server.py

You should see:

Starting MCP server 'Weather MCP Server' with transport 'sse' on http://127.0.0.1:8000/sse

Keep this terminal open.

4. Start the LLM agent (port 8001)

Open a second terminal:

python agent.py

5. Serve the HTML inbox UI (port 8080)

Open a third terminal:

python -m http.server 8080

6. Open the browser UI

Go to: http://localhost:8080/index.html

  1. Wait for status dots to turn green (agent, MCP, LLM)

  2. Type a weather question or click a suggested question

  3. After each query, the MCP tool called bar shows the exact tool the LLM picked (e.g. open_meteo_forecast) and its endpoint

  4. View the HTML-formatted answer below

Inbox UI — Dynamic Tool Display

The UI does not show a fixed tool name before you ask. After each query:

UI element

What it shows

Tool called bar

Exact MCP tool name + Open-Meteo endpoint used for this query

HTML answer card

Groq-formatted weather answer (badge shows the specific tool name)

Suggested questions

Plain questions only — no pre-assigned tool labels

Example after asking "Give me the 5-day forecast for Tokyo":

MCP tool called:  open_meteo_forecast  →  api.open-meteo.com/v1/forecast

5 Suggested Inbox Questions

Question

Tool the LLM typically picks

What's the weather in London right now?

open_meteo_current

Give me the 5-day forecast for Tokyo

open_meteo_forecast

What's the air quality in Paris?

open_meteo_air_quality

What were the coordinates and timezone for New York?

open_meteo_geocode

How was the weather in Sydney yesterday?

open_meteo_historical

The actual tool chosen is shown in the UI after each query — the LLM may pick a different tool if it fits the question better.

CLI Test (all 5 tools)

With server.py running in another terminal:

python test_client.py

Connects via SSE, lists all 5 tools, calls each with a live city, and prints a pass/fail summary. No Groq agent needed for this test.

Project Files

File

Purpose

server.py

MCP server — 5 Open-Meteo endpoint tools, SSE transport

agent.py

Groq LLM agent — picks MCP tool, returns tool_used + HTML

index.html

Inbox UI — status panel, dynamic tool bar, HTML answers

test_client.py

Terminal script to test all 5 MCP tools directly

requirements.txt

Python dependencies

.env.example

Template for Groq API key

Ports Summary

Port

Service

Command

8000

MCP server (SSE)

python server.py

8001

Groq LLM agent

python agent.py

8080

Browser UI

python -m http.server 8080

End Testing

  1. Close the browser tab

  2. Stop the HTML server: Ctrl+C

  3. Stop the agent: Ctrl+C

  4. Stop the MCP server: Ctrl+C

This server cannot be installed

F
license - not found
-
quality - not tested
B
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/RimeetMavani/weather-mcp--build'

If you have feedback or need assistance with the MCP directory API, please join our Discord server