Borrowing it
Nothing to install: this file belongs to SCStelz/security-investigator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SCStelz/security-investigator/main/.github/skills/mcp-usage-monitoring/SKILL.mdgit clone --depth 1 https://github.com/SCStelz/security-investigatorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/scstelz/security-investigator/mcp-usage-monitoring)<a href="https://agentmods.dev/skills/scstelz/security-investigator/mcp-usage-monitoring"><img src="https://agentmods.dev/badge/skills/scstelz/security-investigator/mcp-usage-monitoring/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/scstelz/security-investigator/mcp-usage-monitoring"><img src="https://agentmods.dev/badge/skills/scstelz/security-investigator/mcp-usage-monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 140 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 1837 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Agent Snooping · line 1831 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 1840 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 1860 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Excessive Agency · line 247 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00159 | $0.30419 |
| Opus 5 | $0.00079 | $0.15210 |
| Sonnet 5 | $0.00032 | $0.06084 |
| Haiku 4.5 | $0.00016 | $0.03042 |
Grade A, and why
mcp-usage-monitoring scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 1,866 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Server Usage Monitoring — Instructions
Purpose
This skill monitors and audits Model Context Protocol (MCP) server usage across your Microsoft Sentinel and Defender XDR environment. MCP servers are AI-powered tools that enable language models to interact with Microsoft security services — and like any privileged access channel, they require monitoring.
What this skill tracks:
| MCP Server | Telemetry Source | Key Identifier |
|---|---|---|
| Microsoft Graph MCP Server | MicrosoftGraphActivityLogs |
AppId = e8c77dc2-69b3-43f4-bc51-3213c9d915b4 |
| Sentinel Data Lake MCP | CloudAppEvents |
RecordType 403, Interface = IMcpToolTemplate |
| Sentinel Triage MCP | MicrosoftGraphActivityLogs + SigninLogs |
AppId = 7b7b3966-1961-47b5-b080-43ca5482e21c ("Microsoft Defender Mcp") — dedicated AppId with full user attribution via delegated cert auth |
| Azure MCP Server | AzureActivity |
No dedicated AppId — uses DefaultAzureCredential |
| Sentinel Data Lake — Direct KQL | CloudAppEvents |
RecordType 379, Operation = KQLQueryCompleted |
| Workspace Query Sources (Analytics Tier) | LAQueryLogs |
All clients querying Log Analytics workspace |
What this skill detects:
- Graph API call volume, trends, and endpoint diversity via MCP
- Sensitive/high-risk Graph endpoint access (PIM, credentials, Identity Protection)
- Sentinel workspace query patterns by client application
- User vs. Service Principal attribution across all MCP channels
- Cross-server user analysis — identifies users with broadest MCP footprint (multiple server types, highest call volume)
- Azure ARM operations potentially originating from Azure MCP Server
- Non-MCP platform query sources for governance context (Sentinel Engine, Logic Apps)
- Sentinel Data Lake MCP tool usage — tool call breakdown (
query_lake,list_sentinel_workspaces,search_tables, etc.), success/failure rates, execution duration, tables accessed viaCloudAppEvents(Purview unified audit) - MCP-driven vs Direct KQL delineation — distinguishes Data Lake queries initiated via MCP tools (RecordType 403, Interface
IMcpToolTemplate) from direct KQL queries (RecordType 379) and Analytics tier queries (LAQueryLogs) - Anomalous access patterns: new users, new endpoints, volume spikes, error surges
- MCP server usage as a proportion of total workspace activity
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 1,866 lines · 159 tokens per session scan A 9ca84187a7de
mcp-usage-monitoring is a skill published in the GitHub repository SCStelz/security-investigator (245 stars, last pushed 4d ago), licensed MIT. It adds 159 tokens to every session and 30,419 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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