Individual skill

ai-mcp-security

Assess Model Context Protocol (MCP) servers and agent tool integrations — tool poisoning, prompt injection via tool descriptions/results, over-broad scopes, and unauth tool exposure. Load when the target uses MCP servers, agent tool/function integrations, or connectors. Signals: mcp.json, MCP server, tool schemas, connector marketplace, agent with external tools.

skills/ai-ml/ai-mcp-security/SKILL.md

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Last checked: Nov 7, 2026

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Repository stars (not skill ratings): 27
Repository last updated: Oct 14, 2026
License: MIT

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agent-skills Repository topic
ai-agents Repository topic
ai-security Repository topic
application-security Repository topic
blue-team Repository topic
bug-bounty Repository topic
claude-code Repository topic
codex Repository topic
detection-engineering Repository topic
gemini Repository topic
security Derived category

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# MCP / agent tool-integration security

## When it applies
The system connects an LLM/agent to tools via **MCP** (Model Context Protocol) servers or similar
function/connector integrations. These are the agent's hands — and a fast-moving, under-hardened surface.

## Why it works
The agent reads tool **names, descriptions, and results as trusted context** — so a malicious tool
(or a compromised legitimate one) can inject instructions ("tool poisoning") that hijack the agent.
Tools often run with broad scopes and weak auth, and third-party MCP servers are an unvetted
supply chain. The confused-deputy problem (→ `ai-agent-tool-abuse`) applies at the protocol level.

## Method
1. **Enumerate the tools/servers**: read `mcp.json`/config; list connected servers, their tools,