Your PMs love Amplitude. Now their agents do too.

Headless Amplitude makes your product intelligence composable. Your analytics, cohorts, experiments, replays, and user profiles all become building blocks your own tools and agents can call via MCP and CLI, so you can wire product context into whatever agentic system you’re building. Ask questions, investigate, or take action from tools like Claude, Cursor, Codex, Linear, Slack, Notion, your terminal, or your own agents.

Nope. It removes the need to open it for every question, investigation, or action. The UI remains the system of record for your team: where artifacts live, where governance happens, and where everyone aligns on what a metric means. Headless is a front door into the building.

Mostly you won’t think about it. Ask in your AI client via MCP, and when a request needs an exact, repeatable command, the agent can delegate to the CLI behind the scenes. If you want to drive the CLI yourself in your terminal or CI, that works too.

Amplitude’s MCP gives your agents behavioral context, including the journeys, cohorts, funnels, experiment results, and session replays behind how your users actually behave, on top of a taxonomy your team already curated. Ask yourself: When your coding agent proposes a change to your product, what does it actually know about your users? For most tools, nothing. Headless Amplitude changes that.

Anyone who wants to bring Amplitude’s product intelligence inside the tools and systems they already use. Product managers can ask questions in Claude or ChatGPT. Developers can bring behavioral context into coding agents and automated workflows. AI builders can compose Amplitude into the rest of their stack.

Two kinds of things:

• Read and analyze: Search your Amplitude content, query behavior and retention, inspect experiment results, pull session replays, and dig into customer feedback.
• Take action: Build cohorts, run experiments, ship feature flags, define metrics, and manage events, taxonomy, dashboards, and notebooks.

Plenty. Here are the ones you’ll reach for most:

• Query analytics: query_amplitude_data
• Look up a user: get_amp_user_data
• Build a cohort: use_amplitude_cohorts
• Run experiments and ship flags: use_amp_experiments, use_amp_flags
• Debug with session replay: get_amp_session_replay_info
• Manage events and taxonomy: manage_amp_events, manage_amp_data_taxonomy

…plus define metrics, build dashboards and notebooks, monitor changes, and read customer feedback. See the full tool list in our MCP docs.

Nope. Connect Amplitude to any MCP-capable AI client and ask, investigate, and take action in plain language. If you’d rather work in the terminal, the CLI is there for exact, repeatable commands.

Amplitude MCP uses OAuth and respects your existing permissions. Admins control access at the org and project level, down to separate read and write permissions. Your agents don’t get access to anything you couldn’t already reach.

No, Amplitude doesn’t train AI models on your data. With headless, the model lives in your own AI client (Claude, Cursor, ChatGPT, etc.). Amplitude just serves the data your agent asks for. We don’t see or store your prompts, and we capture usage metrics, not your content.

Amplitude MCP has no separate per-user, per-connection, or per-tool-call charge. It’s included in every Amplitude plan, including Free. Customers’ normal Amplitude plan limits still apply. You may separately consume or pay for usage in the AI client that you connect to, such as Claude or ChatGPT, under that provider’s plan and usage policy

Use our MCP setup documentation to add the MCP server to your AI client in about two minutes.