Connect
Optimize
Secure
Open-Meteo MCP Server
for AI Agents
Production-ready Open-Meteo MCP server with extensible actions — plus built-in authentication, security, and optimized execution.
Open-Meteo MCP Server
Built by 
StackOne
StackOne 
Coverage
6 Agent Actions
Create, read, update, and delete across Open-Meteo — and extend your agent's capabilities with custom actions.
Authentication
Agent Tool Authentication
Per-user OAuth in one call. Your Open-Meteo MCP server gets session-scoped tokens with zero credentials stored on your infra.
Agent Auth →
Security
Agent Protection
Every Open-Meteo tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.
Prompt Injection Defense →
Performance
Max Agent Context. Min Cost.
Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every Open-Meteo call.
Tools Discovery →What is the Open-Meteo MCP Server?
A Open-Meteo MCP server lets AI agents read and write Open-Meteo data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Open-Meteo MCP server ships with pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, and optimized agent context. Connect it from MCP clients like Claude Desktop, Cursor, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.
All Open-Meteo MCP Tools and Actions
Every action from Open-Meteo's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.
Air Qualitys
- Get Air Quality
Get air quality data for a location
Locations
- Search Locations
Search for locations by name using the geocoding API
Elevations
- Get Elevation
Get elevation data for given coordinates
Marine Weathers
- Get Marine Weather
Get marine weather forecast data for a location
Weather Forecasts
- Get Weather Forecast
Get weather forecast data for a location
Historical Weathers
- Get Historical Weather
Get historical weather data for a location and date range
Set Up Your Open-Meteo MCP Server in Minutes
One endpoint. Any framework. Your agent is talking to Open-Meteo in under 10 lines of code.
MCP Clients
Agent Frameworks
JSON{
"mcpServers": {
"stackone": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://api.stackone.com/mcp?x-account-id=<account_id>",
"--header",
"Authorization: Basic <YOUR_BASE64_TOKEN>"
]
}
}
}Open-Meteo MCP Server Resources
MCP Code Mode: Keeping Tool Responses Out of Agent Context
Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.
11 min
Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery
Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.
10 min
Indirect Prompt Injection Defense for MCP Tools: A Technical Guide
MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.
12 min
Open-Meteo MCP Server FAQ
Open-Meteo MCP server vs direct API integration — what's the difference?
A Open-Meteo MCP server and direct API integration serve different use cases. Direct API integration is for software-to-software — backend code calling Open-Meteo. A Open-Meteo MCP server is for AI agents — MCP clients like Claude and Cursor, plus framework agents built with OpenAI, LangChain, or Vercel AI — discovering and calling Open-Meteo at runtime. StackOne provides both.
How does Open-Meteo authentication work for AI agents?
Open-Meteo authentication for AI agents works through a StackOne Connect Session. Create one via the dashboard or the SDK — you get an auth link and ready-to-paste config for Claude Desktop, Cursor, and other MCP clients. Your user authenticates their own Open-Meteo account; StackOne handles token exchange, storage, and refresh. Credentials never reach the LLM, and each user is isolated via
origin_owner_id.Are Open-Meteo MCP tools vulnerable to prompt injection?
Yes — Open-Meteo MCP tools can be vulnerable to indirect prompt injection. Any tool that reads user-written content — documents, messages, tickets, records, or free-text fields — is a potential vector. StackOne Defender scans every tool response before it enters the agent's context — regex patterns in ~1ms, then a MiniLM classifier in ~4ms. 88.7% accuracy, CPU-only.
What is the context bloat of a Open-Meteo agent and how do I avoid it?
Context bloat happens when Open-Meteo tool schemas and API responses eat your Open-Meteo agent's memory, preventing it from reasoning effectively. A single Open-Meteo query can return a massive JSON response, and connecting multiple tools compounds the problem. Tools Discovery and Code Mode reduce context bloat — loading only relevant tools per query and keeping raw responses out of the agent's context.
Can I limit which actions my Open-Meteo agent can access?
Yes — you can limit which actions your Open-Meteo agent can access directly from the StackOne dashboard. Toggle actions on or off, or restrict them to specific accounts, with no code changes to your agent. Session tokens can be scoped to exact actions so if one leaks, exposure stays contained.
Can I create custom agent actions for my Open-Meteo MCP server?
Yes — you can create custom agent actions for your Open-Meteo MCP server using Connector Builder. It's an integration agent your coding assistant (Claude Code, Cursor, or Copilot) can invoke to research Open-Meteo's API, generate production-ready connector YAML, test against the live API, and validate before you ship.
When should I NOT use a Open-Meteo MCP server?
Skip a Open-Meteo MCP server if your integration is purely software-to-software — direct Open-Meteo API integration is simpler when no AI agent is involved. For deterministic, compliance-critical operations (financial transactions, regulatory reporting), direct API gives you predictable behavior without agent-driven decision-making. MCP shines when AI agents need to dynamically discover and call Open-Meteo actions at runtime.
What AI frameworks and AI clients does the StackOne Open-Meteo MCP server support?
The StackOne Open-Meteo MCP server supports both. MCP clients (paste-and-go apps): Claude Desktop, Claude Code, Cursor, VS Code, Goose. Agent frameworks (code SDKs you build with): OpenAI Agents SDK, Anthropic, Vercel AI, Google ADK, CrewAI, Pydantic AI, LangChain, LangGraph, Azure AI Foundry.
Put your AI agents to work
All the tools you need to build and scale AI agent integrations, with best-in-class connectivity, execution, and security.