MCP

The PostHog MCP server exposes Replay Vision through a set of tools your AI coding agent can call directly – author scanners, trigger observations on demand, and read results without leaving your editor.

This works in any MCP client – Cursor, Codex, Claude Code, Windsurf, VS Code, and others.

What you can do

• Author a scanner from your editor – describe what to look for in natural language and have the agent draft the scanner config, project the per-month volume, and create it.
• Trigger an observation on demand – scan a specific session you're investigating without switching to the app.
• Read observations as part of a coding task – pull the structured result and the model's reasoning into context as the agent works.
• Audit a scanner – list its recent observations to decide whether the prompt or filters need tuning.

The tools, by job

Replay Vision's MCP tools are all prefixed vision-. They fall into a few groups – see the overview for what scanners and observations are.

Authoring scanners

• vision-scanners-list – list every scanner in the project.
• vision-scanners-get – read one scanner's config.
• vision-scanners-create – create a new scanner.
• vision-scanners-update – edit an existing one.
• vision-scanners-delete – remove one.

Sizing before you create

• vision-scanners-estimate-create – project the per-month observation volume of a hypothetical scanner before you commit to it.
• vision-quota-retrieve – check the remaining monthly quota.

Pair these two before calling vision-scanners-create to avoid creating a scanner that would immediately blow the budget.

Triggering an observation on demand

• vision-scanners-scan-session – run a specific scanner against a specific session right now. Same code path as the Scan this recording action in the replay player.

The call queues the observation asynchronously and returns immediately; the actual scan takes a few minutes. Poll vision-scanners-observations-list to find the result once it lands.

Reading observations

For a specific session (across all scanners):

• vision-observations-list – every observation any scanner produced for one session.
• vision-observations-retrieve – fetch one observation by ID.

For one scanner (across sessions):

• vision-scanners-observations-list – paginated list of a scanner's observations.
• vision-scanners-observations-get – fetch one of that scanner's observations by ID.

Impact and cohorts

• vision-scanners-impact-retrieve – get affected sessions and users for a scanner over a trailing window. Monitors count verdict-yes observations. Classifiers require a tag parameter. Scorers require min_score and/or max_score.
• vision-scanners-affected-cohort-create – save the affected users as a static cohort. Same qualifiers as the impact endpoint. The cohort is a dated snapshot and doesn't live-update.

Example prompts

Try these with your MCP-enabled agent:

• How many users were affected by my "Dead-end pages" monitor in the last 30 days?
• Create a cohort from the users my "User intent" classifier tagged as support_seeking.
• Create a Replay Vision scanner that flags sessions where users get stuck on the /checkout page, narrow to enterprise customers, and start at 25% sampling. Estimate the cost first.
• Scan session abc123 with the "Dead-end pages" scanner and tell me what it found, including the reasoning.
• List the last 20 observations from my "Frustration score" scanner and summarize what's driving high scores.
• Find every Replay Vision observation for session abc123 and give me a one-line summary of each.
• How much Replay Vision quota do we have left this month?
• How many users did my "Dead-end pages" monitor affect in the last 14 days? Save them as a cohort.

See the MCP server docs for client setup, and the Replay Vision overview for product concepts.