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 skills add antongulin/agenticflow-ai-skills --skill agenticflow-mcpgit clone --depth 1 https://github.com/antongulin/agenticflow-ai-skillsWrote 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/skills/antongulin/agenticflow-ai-skills/agenticflow-mcp)<a href="https://agentmods.dev/skills/antongulin/agenticflow-ai-skills/agenticflow-mcp"><img src="https://agentmods.dev/badge/skills/antongulin/agenticflow-ai-skills/agenticflow-mcp/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/skills/antongulin/agenticflow-ai-skills/agenticflow-mcp"><img src="https://agentmods.dev/badge/skills/antongulin/agenticflow-ai-skills/agenticflow-mcp.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 | $0.00158 | $0.01571 |
| Opus 5 | $0.00079 | $0.00785 |
| Sonnet 5 | $0.00032 | $0.00314 |
| Haiku 4.5 | $0.00016 | $0.00157 |
Grade A, and why
agenticflow-mcp 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 11d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgenticFlow MCP
Do NOT install the legacy
agenticflow-mcpstandalone server repo. It is stale (last release lags the current platform by many versions) and is not the recommended integration path. Everything below uses theafCLI (install vianpm install -g @pixelml/agenticflow-cli), which covers MCP operations comprehensively and stays in lockstep with platform changes.
MCP (Model Context Protocol) clients are the tool-provider layer that lets an agent read or write external systems — Google Docs, Google Sheets, Slack, Notion, GitHub, Apify, Gmail, Pinterest, YouTube, and many more. A workspace usually has many MCP clients already configured; your job is to pick the right one and verify it's safe before attaching to an agent.
Orient first
Before touching MCP clients, run:
af bootstrap --json
Extract auth.workspace_id + _links.mcp (the web UI URL for MCP management). Surface _links.mcp to the user: "Your MCP connections live at <_links.mcp> — you can add or re-authenticate providers there if any inspections fail." If data_fresh: false, the backend is degraded — don't mutate.
Discovery & health
af changelog --json # What's new in the CLI since your last install
af context --json # AI agent orientation, env vars, invocation guidance
af bootstrap --strict --json # Health check — exits non-zero if degraded
af bootstrap returns an invocation block telling you the correct CLI binary to use. af bootstrap --strict exits non-zero when the backend is unhealthy, so CI/automation can abort before mutating against a degraded workspace.
The one pattern that matters: inspect before attach
Not all MCP clients are equal. There are two major families, and one of them breaks on writes.
af mcp-clients list --name-contains "google sheets" --fields id,name,is_authenticated --json
af mcp-clients inspect --id <mcp_client_id> --json
af mcp-clients get --id <mcp_client_id> --json # Alias for inspect (v1.8.1+)
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.
- 11d ago First seen · 119 lines · 158 tokens per session scan A 0f4e8cad2d4d
agenticflow-mcp is a skill published in the GitHub repository antongulin/agenticflow-ai-skills (2 stars, last pushed 6d ago), licensed MIT. It adds 158 tokens to every session and 1,571 once invoked, about $0.0008 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.
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