by reatlat
# Add to your Claude Code skills
git clone https://github.com/reatlat/fullstory-claude-pluginGuides for using mcp servers skills like fullstory-claude-plugin.
fullstory-claude-plugin is an open-source mcp servers skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by reatlat. It has 57 GitHub stars.
fullstory-claude-plugin's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/reatlat/fullstory-claude-plugin" and add it to your Claude Code skills directory (see the Installation section above).
Yes. SkillsLLM lists many other MCP Servers skills you can browse and compare side by side. Open the MCP Servers category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh fullstory-claude-plugin against similar tools.
No comments yet. Be the first to share your thoughts!
Top skills in this category by stars
Unlocks once the catalog security scan passes (runs nightly).
The deep catalog scan for this skill is still queued. Run an instant dependency check now instead.
Talk to your product data.
Ask Claude anything about your users — drop-offs, rage clicks, conversion funnels — and get answers backed by real sessions.
One command in Claude Code:
/plugin marketplace add reatlat/fullstory-claude-plugin
/plugin install fullstory-reatlat@fullstory-marketplace
Also works in Cursor (Marketplace panel, same URL) and VS Code Copilot (Chat: Install Plugin from Source).
No local server. No API keys to juggle. OAuth handles auth — you sign in once and it just works.
Claude Desktop doesn't support the plugin marketplace — you get the MCP tools but not the skills/agents. Add this to claude_desktop_config.json:
{
"mcpServers": {
"fullstory": {
"type": "http",
"url": "https://api.fullstory.com/mcp/fullstory"
}
}
}
Config file locations: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS), %APPDATA%\Claude\claude_desktop_config.json (Windows). Restart Claude Desktop after editing.
Fullstory records every session on your site. This plugin lets Claude read that data.
Before: Export CSV → pivot table → screenshot → Slack → someone asks "but why?" → repeat.
After: Type a question. Get an answer.
| You ask | Claude does |
|---|---|
| "What's the top frustration on our product right now?" | Builds a rage-click metric across all pages, surfaces the worst offenders, pulls sessions to show you exactly what users are clicking |
| "How many users abandoned checkout last month, by device?" | Resolves or builds a funnel metric, attaches segment, computes, returns a table with percentages |
| "Show me sessions where enterprise users hit errors on settings" | Builds enterprise segment, finds error sessions, reads each transcript in isolation, synthesizes patterns |
| "Is our new onboarding flow actually reducing drop-off?" | Trend metric comparing before/after deploy date, with statistical context |
| "Find session #abc123 and tell me why the submit button didn't work" | Opens session, steps through key moments, diffs before/after the click, reports what broke |
It doesn't just answer "how many." It answers "why" — by reading the actual sessions behind the numbers.
See a real conversation → — 10 skills, one investigation, zero SQL.
Forty-four skills ship with the plugin. Claude loads the right one automatically based on what you ask.
| Skill | Trigger | What it does |
|---|---|---|
quick-stats |
"How many users yesterday?" | One-number answers. Build → compute → present. No analysis overhead. |
general-analysis |
Any quantitative question | Full workflow: classify intent, search/build, compute, validate, investigate |
comparisons |
A vs B questions (auto) | Picks dimensionality vs segments correctly — prevents silent wrong results |
funnel-doctor |
"Where are users dropping off?" | Funnel step analysis, drop-off quantification, session evidence for why |
weekly-digest |
"What changed this week?" | Structured report: frustrations, errors, conversion, traffic — week-over-week |
page-performance |
"Which page has the most errors?" | Page-level health: error rates, device breakdown, navigation patterns |
experiment-analyzer |
"Did the variant win?" | A/B test analysis: impact, significance assessment, segment breakdown, side effects |
retention-analyzer |
"Are users coming back?" | N-day retention, cohort stickiness, churn signals, engagement depth |
anomaly-detector |
"Did anything unusual happen?" | Proactive scan: spikes, drops, pattern breaks across all key metrics |
campaign-tracker |
"How did the email campaign perform?" | UTM-tagged traffic, landing page conversion, channel comparison, ROI signals |
feature-adoption |
"Are users using the new feature?" | Adoption funnel: awareness → trial → adoption → retention, segment breakdown |
benchmark-analyzer |
"What's our baseline conversion rate?" | Historical baselines, target setting, progress tracking, industry context |
dashboard-builder |
"Set up a product health dashboard" | Curated KPI dashboards with north star metrics, auto-saved for weekly review |
predictive-alerts |
"Warn me before conversion drops too low" | Trend projection, threshold breach prediction, early warning system |
persona-builder |
"What types of users do we have?" | Behavioral personas from real session data, data-driven user profiles |
lifecycle-analyzer |
"How many users are at risk of churning?" | New → active → at-risk → churned lifecycle mapping with transition rates |
onboarding-tutor |
"I'm new — how do I use this?" | Interactive onboarding, role-specific guides, first query walkthrough |
query-translator |
"How do I measure user happiness?" | Translates vague business questions into measurable Fullstory queries |
nps-proxy |
"What's our user satisfaction?" | Behavioral NPS alternative — satisfaction proxy from frustration/engagement signals |
| Skill | Trigger | What it does |
|---|---|---|
frustration-hunter |
"What's frustrating users?" | Rage clicks, dead clicks, form abandonment — ranked, with session evidence |
error-forensics |
"What's breaking in production?" | JS errors, network failures, console exceptions — root cause from sessions |
session-review |
Session URL or bug report | Open → view → diff → close. Visual replay without a video player |
session-search |
"Find sessions for user 84721" | Search by user ID, device, browser, page, custom event |
user-journey |
"Trace user@example.com's sessions" | Multi-session timeline, friction points, churn signals |
jira-bug-reporter |
"File a bug for this session" | Auto-populated bug reports with session URL, errors, repro steps, severity |
customer-360 |
"Show me everything about this user" | Full customer snapshot: sessions, purchases, errors, engagement trajectory |
form-analyzer |
"Which form field causes drop-off?" | Field-by-field abandonment, validation errors, time-to-complete, mobile forms |
mobile-analyzer |
"How's the mobile experience?" | Touch targets, viewport issues, responsive bugs, mobile vs desktop gap |
scroll-depth-analyzer |
"Are users reading to the bottom?" | Content visibility, CTA placement, where users stop scrolling per page |
heatmap-generator |
"What do users click on most?" | Element-level interaction density, dead click zones, rage click hotspots |
a11y-analyzer |
"Can keyboard users navigate this?" | Keyboard traps, focus order, missing labels, WCAG audit from real sessions |
api-monitor |
"Are API errors affecting users?" | Endpoint latency, error rates, API-driven UX failures, backend deploy impact |
session-playlist |
"Bundle these sessions for the team" | Curate annotated playlists with timestamps, narratives, and key moments |
changelog-detective |
"What actually changed after the deploy?" | Diff errors, frustrations, and behaviors before/after — catch undocumented changes |
| Skill | Trigger | What it does |
|---|---|---|
deploy-radar |
"I just deployed — did anything break?" | Before/after comparison: errors, conversion, frustrations |
metric-auditor |
"Clean up our metrics" (auto) | Find duplicates, stale segments, misconfigured objects |
cohort-compass |
Cohort analysis (auto) | Build, track, reuse segments across analyses |
annotation-ops |
"Mark the deploy on the timeline" (auto) | Create deploy markers, experiment windows, incident tags |
revenue-impact |
"What does this cost us?" (auto) | Attach dollar estimates to UX issues and conversion drops |
segment-wizard |
"Help me build a segment for..." | Guided interactive cohort building for non-technical users |
privacy-auditor |
"Are we capturing PII?" | Audit session capture for PII leaks, verify masking and exclusion rules |
webhook-health |
"Are our webhooks delivering?" | Webhook delivery monitoring, integration health, data pipeline verification |
slack-reporter |
"Send this to #product-engineering" | Format findings as scannable Slack messages with evidence links and action items |
incident-responder |
"We have an incident — checkout is down" | Structured response: triage, blast radius, session evidence, status updates |
| Agent | What it does |
|---|---|
session-context |
Reads a single session transcript in isolation — keeps main context clean |
batch-session-reader |
Reads multiple sessions in parallel — 5x faster for investigation workflows |
Without StoryAI enabled, the server connects but exposes zero tools. If you see "connected but no tools," that's the fix.
You → Claude Code → Fullstory MCP Server (api.fullstory.com) → Your Fullstory Data
↑ OAuth, no local process
The plugin wires up three things:
| File | Role |
|---|---|
.mcp.json |
Points Claude at https://api.fullstory.com/mcp/fullstory |
skills/*/SKILL.md |
Teaches Claude how to think about Fullstory data — mental models, workflows, edge cases |
agents/*.md |
Isolated context workers for heavy lifting (session transcripts) |
The MCP server exposes tools lik