Borrowing it
Nothing to install: this file belongs to redhat-community-ai-tools/dci-mcp-server. 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/redhat-community-ai-tools/dci-mcp-server/main/AGENTS.mdgit clone --depth 1 https://github.com/redhat-community-ai-tools/dci-mcp-serverWrote 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/redhat-community-ai-tools/dci-mcp-server/agents-md)<a href="https://agentmods.dev/instructions/redhat-community-ai-tools/dci-mcp-server/agents-md"><img src="https://agentmods.dev/badge/instructions/redhat-community-ai-tools/dci-mcp-server/agents-md/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/instructions/redhat-community-ai-tools/dci-mcp-server/agents-md"><img src="https://agentmods.dev/badge/instructions/redhat-community-ai-tools/dci-mcp-server/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.04917 | $0.04917 |
| Opus 5 | $0.02459 | $0.02459 |
| Sonnet 5 | $0.00983 | $0.00983 |
| Haiku 4.5 | $0.00492 | $0.00492 |
Grade A, and why
dci-mcp-server 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 9d 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 — 378 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Overview
This is an MCP (Model Context Protocol) server that provides AI assistants with tools to interact with:
- DCI (Distributed CI): Red Hat's distributed continuous integration system
- GitHub: Issues, PRs, and repository information
- GitLab: Issues, merge requests, diffs, and project information
- Jira: Ticket data with comments and changelog
- Google Drive: Document creation from DCI reports
- Red Hat Support Cases: Case data from the Customer Portal
The server is built with FastMCP and supports multiple transport modes (stdio for CLI/IDE integration, SSE/HTTP for web applications).
Architecture
Core Components
-
Services (
mcp_server/services/): Business logic for external APIs- All DCI services inherit from
DCIBaseServicewhich handles authentication (API key or login/password) - Each service encapsulates API interactions for a specific domain (jobs, components, files, etc.)
- External services:
github_service.py,jira_service.py,google_drive_service.py,support_case_service.py
- All DCI services inherit from
-
Tools (
mcp_server/tools/): MCP tool definitions that wrap service methods- Tools are registered conditionally in
mcp_server/main.pybased on available credentials - Each tool file exports a
register_*_tools(mcp)function - Naming convention:
<domain>_tools.py(e.g.,job_tools.py,github_tools.py)
- Tools are registered conditionally in
-
Prompts (
mcp_server/prompts/): Parameterized prompts for common workflows/dci/rca <job_id>: Root cause analysis workflow/dci/weekly <subject>: 7-day analysis report/dci/biweekly <subject>: 14-day analysis report/dci/quarterly <remoteci>: 3-month comprehensive analysis with statistics
-
Entry Points:
main.py: CLI entry point that readsMCP_TRANSPORTenv var (stdio|sse|http)mcp_server/main.py: Creates and configures the FastMCP server instance
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.
- 9d ago First seen · 378 lines · 4,917 tokens per session scan A e91de5e3b22c
dci-mcp-server AGENTS.md is an instructions file published in the GitHub repository redhat-community-ai-tools/dci-mcp-server (1 stars, last pushed today), licensed Apache-2.0. It adds 4,917 tokens to every session, about $0.0246 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 2026-08-31.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.