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.
npx agentmods add instructions/zenml-io/mcp-zenml/agents-mdgit clone --depth 1 https://github.com/zenml-io/mcp-zenmlWrote 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/instructions/zenml-io/mcp-zenml/agents-md)<a href="https://agentmods.dev/instructions/zenml-io/mcp-zenml/agents-md"><img src="https://agentmods.dev/badge/instructions/zenml-io/mcp-zenml/agents-md.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00694 | $0.00694 |
| Opus 5 | $0.00347 | $0.00347 |
| Sonnet 5 | $0.00139 | $0.00139 |
| Haiku 4.5 | $0.00069 | $0.00069 |
Grade A, and why
mcp-zenml AGENTS.md 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 6d 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
Project Structure & Module Organization
server/– MCP server implementation. Main entry:server/zenml_server.py; analytics:server/zenml_mcp_analytics.py; treatserver/lib/as vendored support code (avoid edits unless necessary).scripts/– Developer utilities:format.sh(ruff),test_mcp_server.py(smoke test),test_analytics.py(analytics diagnostics),test_datetime_normalization.py(unit tests).assets/– Images and static assets.- Root files –
README.md,manifest.json,mcp-zenml.mcpb(MCP bundle), CI in.github/workflows/.
Build, Test, and Development Commands
- Run server locally:
uv run server/zenml_server.py - Smoke test (local):
uv run scripts/test_mcp_server.py server/zenml_server.py - Unit tests (local):
uv run scripts/test_datetime_normalization.py - Format & lint:
bash scripts/format.sh(ruff check + import sort + format) - CI mirrors the smoke test via GitHub Actions and requires Python 3.12.
Coding Style & Naming Conventions
- Language: Python 3.12+. Indentation: 4 spaces.
- Use snake_case for functions/variables, PascalCase for classes, UPPER_SNAKE_CASE for constants.
- Keep imports tidy;
scripts/format.shenforces ruff rules and import sorting. - Logging: prefer
loggingto stderr; avoid printing from MCP tool functions except returning strings/JSON. Keep logs minimal to avoid MCP JSON protocol interference.
Testing Guidelines
- Primary test:
scripts/test_mcp_server.pyexercises MCP connection, initialization, and basic tools. - Unit tests:
scripts/test_datetime_normalization.pytests datetime filter normalization and exception classification (no credentials needed). - Analytics tests:
scripts/test_analytics.pytests the analytics pipeline. - Run locally with
uv run scripts/<test_script>.py; CI runs on PRs and a scheduled workflow. - When adding new test scripts, always wire them into
.github/workflows/pr-test.ymlso they run in CI. Tests that don't need ZenML credentials should run unconditionally. - Follow descriptive names (e.g.,
test_<area>_behavior.py) and place underscripts/. Keep tests fast and network-light; mock ZenML calls when feasible.
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.
- 6d ago First seen · 40 lines · 694 tokens per session scan A 24cd032567b2
mcp-zenml AGENTS.md is an instructions file published in the GitHub repository zenml-io/mcp-zenml (49 stars, last pushed 11d ago), licensed MIT. It adds 694 tokens to every session, about $0.0035 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.
Other instructions, from other repositories
unified-ai-system AGENTS.md
AGENTS.md instructions for happy520ai/unified-ai-system, covering repository guidance, ownership, language and module policy, public repository rules and safety.
mcp-router CLAUDE.md
Claude Code instructions for mcp-router/mcp-router, a project described as: A Unified MCP Server Management App (MCP Manager).
portkey-admin-mcp AGENTS.md
AGENTS.md instructions for CodesWhat/portkey-admin-mcp, covering agent instructions and code review.
clearml-mcp CLAUDE.md
Instructions for prassanna-ravishankar/clearml-mcp, covering clearml mcp server, project overview, available tools, task operations and model operations.
blockrun-mcp AGENTS.md
AGENTS.md instructions for BlockRunAI/blockrun-mcp, covering blockrun mcp, commands, project structure, key dependencies and install in codex.
openrouter-mcp-multimodal AGENTS.md
AGENTS.md instructions for stabgan/openrouter-mcp-multimodal, covering agent instructions, before you ship, releasing (read this before publishing), short version and version files (must all match package.json).