agenticflow-mcp
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
More from antongulin/agenticflow-ai-skills
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Create, run, and iterate on a single AgenticFlow AI agent — one chat endpoint, one assistant, one persona. Use when the user wants a customer-facing bot, a support assistant, a single task agent, or a prompt experiment. Choose this skill over agenticflow-workforce when there's no orchestration between roles (no handoff, no coordinator → workers). Covers `af agent create/update/run/delete`, the `--patch` partial-update pattern for iteration, `af schema agent --field <name>` for nested payload shapes (including suggested_messages, mcp_clients, response_format), the `model_user_config` / `code_execution_tool_config` settings, and safe iteration loops.
5agenticflow-workforce
Deploy and operate a multi-agent AgenticFlow workforce — a DAG of agents that hand off to each other (trigger → coordinator → worker agents → output). Use when the user asks for a team, pipeline, or multi-agent system: research-then-write, triage-then-specialist, dev shop, marketing agency, sales team, content studio, support center, Amazon seller team. Choose this skill over agenticflow-agent when the ask mentions 'team', 'workforce', 'pipeline', 'multiple agents', 'delegation', 'handoff', or names a built-in blueprint. Provides the `af workforce *` command surface, blueprint decisions, graph wiring, MCP attach recipes, and public URL publishing.
5agenticflow-llm-models
Select and configure LLM models for AgenticFlow agents and workforces. Use this skill whenever the user asks which model to use, needs reasoning capabilities, wants fast/cheaper options, gets finish_reason=length errors, or asks about model speed/quality/intelligence trade-offs. Covers the top recommended models, upstream canonical models, models to avoid, reasoning configuration, and max_tokens settings.
5agenticflow-built-in-credits
Use AgenticFlow's built-in features and account credits first — before adding external API keys (BYOK). Use this skill whenever the user asks about image generation without API keys, wants to use their existing credits, asks about built-in vs BYOK, or mentions agenticflow_generate_image, web_search, web_retrieval, or credit-efficient workflows. BYOK is only for extension when unsatisfied or explicitly requested.
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