Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/AndrewAltimit/template-repoWrote 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/mcp/andrewaltimit/template-repo/_codex_disabled_security_risk)<a href="https://agentmods.dev/mcp/andrewaltimit/template-repo/_codex_disabled_security_risk"><img src="https://agentmods.dev/badge/mcp/andrewaltimit/template-repo/_codex_disabled_security_risk.svg" alt="Measured on agentmods" height="20"></a>Grade A, and why
_codex_DISABLED_SECURITY_RISK 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 8d 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.
What it actually says
{
"_codex_DISABLED_SECURITY_RISK": {
"_warning": "OpenAI/Codex disabled due to mass surveillance concerns. Use Anthropic models instead. Rename key back to 'codex' to re-enable.",
"command": "docker",
"args": [
"compose",
"-f",
"./docker-compose.yml",
"--profile",
"services",
"run",
"--rm",
"-T",
"mcp-codex",
"mcp-codex",
"--mode",
"stdio"
]
}
}What else .mcp.json configures
This page is one entry in a file that holds 11. Installing the file brings all of them; each is measured and scanned on its own page.
- MCP server agentcore-memory A not measured
- MCP server blender A not measured
- MCP server code-quality A not measured
- MCP server content-creation A not measured
- MCP server crush A not measured
- MCP server gemini A not measured
- MCP server github-board A not measured
- MCP server opencode A not measured
- MCP server reaction-search A not measured
- MCP server sprite-sheet A not measured
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.
- 8d ago First seen · 20 lines scan A a628644a373a
_codex_DISABLED_SECURITY_RISK is an MCP server published in the GitHub repository AndrewAltimit/template-repo (131 stars, last pushed 2mo ago), licensed Unlicense. Its token cost is not measured: an MCP server costs its tool schemas, not its config file. 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.
Other mcp servers, from other repositories
plantuml
MCP server for generating PlantUML diagrams. Runs locally from the plantuml-mcp-server npm package. Needs 1 environment variable to run.
aegis
Auto-instrument AI agent frameworks with runtime security. One line to govern LangChain, CrewAI, OpenAI, Anthropic — injection blocking, PII masking, action policy, audit trail. Zero code changes. Runs locally from the agent-aegis Python package. Needs 1 environment variable to run.
mcp-eu-ai-act
EU AI Act + GDPR compliance scanner. One call, no arguments, 10 seconds. 22 AI frameworks detected. Remote server at mcp.arkforge.tech.
eu-ai-act-scanner
MCP server "eu-ai-act-scanner" as configured in Peaky8linders/eu-ai-act-scanner. Launched with eu-ai-act-scan-mcp.
whitepact
ResponsibleAI — Enterprise AI Governance Platform: trust scoring, bias detection, hallucination detection, guardrails, compliance (NIST AI RMF / EU AI Act / ISO 42001), cost intelligence, drift monitoring. Runs locally from the rai-governance-platform Python package. Needs 1 environment variable to run.
veriswarm-mcp
VeriSwarm MCP Server — Trust infrastructure for AI agents via Model Context Protocol. Runs locally from the veriswarm-mcp Python package.