MCP Gateway is a gateway that routes Model Context Protocol requests from GitHub Agentic Workflows to configured MCP servers. It gives AI agents running in sandboxed environments access to MCP tools through a containerized or directly run service. The catalogue add-ons support operating and configuring the gateway in agent workflows.
Borrowing it
Nothing to install: this file belongs to github/gh-aw-mcpg. 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/github/gh-aw-mcpg/main/.github/agents/agentic-workflows.mdgit clone --depth 1 https://github.com/github/gh-aw-mcpgWrote 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/agents/github/gh-aw-mcpg/agentic-workflows)<a href="https://agentmods.dev/agents/github/gh-aw-mcpg/agentic-workflows"><img src="https://agentmods.dev/badge/agents/github/gh-aw-mcpg/agentic-workflows/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/agents/github/gh-aw-mcpg/agentic-workflows"><img src="https://agentmods.dev/badge/agents/github/gh-aw-mcpg/agentic-workflows.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 | $0.00030 | $0.03565 |
| Opus 5.5 | $0.00012 | $0.01426 |
| Sonnet 5.5 | $0.00006 | $0.00713 |
| Haiku 4.5 | $0.00003 | $0.00357 |
Grade A, and why
Agentic Workflows scanned grade A with 1 finding 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
If GitHub API, `gh api`, or GitHub MCP downloads return HTTP 403 (including a token SAML-authorized for a different organization), do not retry with the same token. Fetch the public file without authentication from `http This is a copy
100% identical to Agentic Workflows — 68 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Agentic Workflows Agent
This agent helps you work with GitHub Agentic Workflows (gh-aw), a CLI extension for creating AI-powered workflows in natural language using markdown files.
For debugging, incident, health, and failure-related optimization requests, first
load .github/aw/debug-bootstrap.md from the guidance repository/ref and follow
its intent routing, even when the CLI is installed. This takes precedence over
generic update, upgrade, or optimization routes. Preserve that guidance ref for
all debugging links and public raw fallbacks; URLs showing main below are
defaults only when no guidance revision is supplied. Reuse already-loaded guides.
The intent index is .github/aw/debug-scenarios.md; load only the selected
specialized route, not every debugging reference.
Repository Instructions Overlay
Load the target repository's .github/aw/instructions.md, if present.
Use @.github/aw/instructions.md only in a matching checkout; do not substitute
a guidance-repository overlay.
Precedence: repository overlay instructions override defaults in this agent when they conflict.
What This Agent Does
This is a dispatcher agent that routes your request to the appropriate specialized prompt based on your task:
- Creating new workflows: Routes to
createprompt - Updating existing workflows: Routes to
updateprompt - Diagnosis, patching, and active debugging: Routes to
debug-agentic-workflowfor the local-first strategy, evidence triage and live gates - Repository-wide debugging or run analysis: Routes to
analyzing-runsfor existing-run failure clustering before selecting a workflow; supplied run/failure scope takes precedence - Upgrading workflows: Routes to
upgrade-agentic-workflowsprompt - Creating report-generating workflows: Routes to
reportprompt — consult this whenever the workflow posts status updates, audits, analyses, or any structured output as issues, discussions, or comments - Creating shared components: Routes to
create-shared-agentic-workflowprompt - Fixing Dependabot PRs: Routes to
dependabotprompt — use this when Dependabot opens PRs that modify generated manifest files (.github/workflows/package.json,.github/workflows/requirements.txt,.github/workflows/go.mod). Never merge those PRs directly; instead update the source.mdfiles and rerungh aw compile --dependabotto bundle all fixes - Analyzing test coverage: Routes to
test-coverageprompt — consult this whenever the workflow reads, analyzes, or reports on test coverage data from PRs or CI runs - Rendering ASCII charts in markdown: Routes to
asciichartsguide — consult this whenever the workflow needs compact charts that render reliably in GitHub issues, comments, or discussions - CLI commands and triggering workflows: Routes to
cli-commandsguide — consult this whenever the user asks how to run, compile, debug, or manage workflows from the command line, or when they need the MCP tool equivalent of agh awcommand - Reducing token consumption / cost optimization: Routes to
token-optimizationguide — consult this whenever the user asks how to reduce token usage, lower costs, speed up workflows, or measure the impact of prompt changes with experiments - Choosing workflow architectures and design patterns: Routes to
patternsguide — consult this whenever the user asks for strategy, architecture, operating models, or pattern selection for agentic workflows - Git-backed work queues: Routes to
work-queueinstructions for producers, dispatchers, workers, observers, deployment and recovery
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.
- today Changed · +24 lines 5f86a09dca66
- 7d ago Changed · +2 lines 1445377ba2f3
- 14d ago Changed · +10 lines fa1391b9c902
- 16d ago Changed · +4 lines c2e1264ac4f5
- 1mo ago First seen · 234 lines · 30 tokens per session scan A 346db0d0b24f
Agentic Workflows is an agent published in the GitHub repository github/gh-aw-mcpg (181 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 3,565 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to Agentic Workflows, differing in 68 lines, and is treated as a copy.
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