AI & Intelligence

The AI layer: which model backends a platform may use, how usage is metered, and the surfaces that consume them (the Agent step, the MCP server, the copilot). Glossary of the terms that only mean something here; each page below holds the detail.

🔌 AI Provider

A configured LLM backend (OpenAI, Anthropic, Google, Azure, OpenRouter, Cloudflare, Custom, or Activepieces-hosted) with encrypted credentials, resolved per platform.

🪙 AI Credits

The metered currency for AI usage — 1000 credits = $1 — backed by per-key OpenRouter limits. A quota, not a wallet.

• Avoid: "tokens" for the billing unit; tokens are the model's unit, credits are ours.

🤖 Agent

A flow step that runs an autonomous LLM loop rather than a single call. Its AgentTools are Piece, Flow, MCP, or Knowledge Base handles.

🔗 MCP Server

The per-project endpoint that exposes Activepieces tools to an external AI assistant. Distinct from a piece that calls an MCP server.

Pages

• AI Providers — configuring backends, credential storage, credit metering
• AI Agents — the Agent step and its tool types
• MCP Server — the per-project endpoint, tool exposure, visibility rules
• AI & MCP — how the AI and MCP surfaces fit together

Related

Knowledge Base lives in Data, Storage & Observability — it is a document store first, an AI tool second.