Weather MCP (Open-Meteo) — agentic threat model
The Weather MCP is a low-risk, read-only utility with minimal agentic capabilities, presenting primary risks around indirect prompt injection via external weather data and basic tool-integration vulnerabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.10 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.10 | |
| Opacity & Reflexivity | 0.10 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Not certain from the listing — The tool does not include a foundation model itself. However, the consuming LLM is vulnerable to indirect prompt injection if malicious payloads are embedded in the weather data returned by the external API.
Not certain from the listing — The tool acts as a transient data pipeline fetching real-time weather from Open-Meteo. There is no persistent vector store or training data, but there is a minor risk of data poisoning if the upstream API is compromised.
Integrates via the Model Context Protocol (MCP). The primary risk is insecure tool integration, where an orchestrator might fail to sanitize input parameters (e.g., city names), potentially leading to injection or SSRF depending on how the connector is implemented.
Not certain from the listing — The tool runs as an MCP server. While it requires no API keys or secrets (reducing credential theft risk), the hosting environment must still be secured against standard container or host-level compromises.
Not certain from the listing — There are no mentioned logging, monitoring, or guardrail mechanisms to detect anomalous inputs or outputs passing through this connector.
The tool operates without authentication or API keys. While this eliminates credential management overhead, it lacks built-in access controls, relying entirely on the host platform's security boundary.
As an open MCP tool, it can be easily integrated into multi-agent systems. The main ecosystem risk is cascading logic failures if downstream agents implicitly trust the weather data without validation.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).