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/techskies11/datadog-mcpWrote 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/rules/techskies11/datadog-mcp/mcp-architecture)<a href="https://agentmods.dev/rules/techskies11/datadog-mcp/mcp-architecture"><img src="https://agentmods.dev/badge/rules/techskies11/datadog-mcp/mcp-architecture.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 | $0.00000 | $0.02660 |
| Opus 5 | $0.00000 | $0.01330 |
| Sonnet 5 | $0.00000 | $0.00532 |
| Haiku 4.5 | $0.00000 | $0.00266 |
Grade A, and why
mcp-architecture 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 — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Server Architecture
This file documents the actual architecture of this repo. Follow it for any new
domain/tool - don't reintroduce patterns from older revisions of this server
(a single monolithic server.py, TypedDict responses, or an implicit
"create auth if not passed" factory) even if you've seen them in git history.
Project Structure
datadog-mcp/
├── src/
│ └── datadog_mcp/
│ ├── __init__.py
│ ├── server.py # Composition ONLY: wires domains + resources/prompts
│ ├── auth.py # DatadogAuth + get_auth_instance() singleton
│ ├── tools/ # One module per Datadog domain
│ │ ├── logs.py
│ │ ├── aggregations.py
│ │ ├── metrics.py
│ │ ├── dashboards.py
│ │ ├── apm.py
│ │ ├── monitors.py
│ │ └── downtimes.py
│ └── utils/ # Shared, domain-agnostic utilities
│ ├── auth.py # get_api_instance() factory
│ ├── annotations.py # ToolAnnotations presets
│ ├── pagination.py # Page-size constants/clamping
│ ├── response.py # Pydantic response base classes + helpers
│ └── time.py # parse_time_value()
├── tests/ # Mirrors src/ (tests/tools/test_<domain>.py, tests/utils/)
├── pyproject.toml
└── README.md
Separation of Concerns
Server Layer - Composition Only
server.py never contains a tool implementation, a Pydantic model, or a call
to a Datadog API class directly. It only imports each domain's
register_<domain>_tools and calls it, plus defines @mcp.resource/@mcp.prompt
(which are thin enough to live here).
# server.py
from fastmcp import FastMCP
from datadog_mcp.tools.logs import register_logs_tools
from datadog_mcp.tools.metrics import register_metrics_tools
# ... one import per domain
mcp = FastMCP("Datadog Integration")
register_logs_tools(mcp)
register_metrics_tools(mcp)
# ...
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 · 272 lines · 0 tokens per session scan A 0beffb6b1941
mcp-architecture is a cursor rule published in the GitHub repository techskies11/datadog-mcp (0 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,660 tokens. 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 2026-08-31.
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