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One MCP connection. Full Firebase context. No more console diving — just ask.
Stop writing Firestore queries and digging through the Firebase console. Ask your AI agent to pull user data, event funnels, retention metrics, and collection-level analytics — across projects and environments.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Go beyond read-only. Your AI agent can write documents to Firestore, update user properties, trigger Cloud Functions, and manage configuration — from a single conversational prompt.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Set AI-powered watches on your Firebase data. Get alerts on user drop-off spikes, event anomalies, collection growth rates, and authentication failure surges — before they become incidents.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Go beyond read-only. Your AI agent can write documents to Firestore, update user properties, trigger Cloud Functions, and manage configuration — from a single conversational prompt.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
Getting answers from Firestore means writing queries in the Firebase console SDK or building a custom data pipeline. Non-engineering team members can't self-serve basic questions like 'how many users signed up this week?' without filing a data request.
Ask your AI agent a question in plain English. It translates the intent into a Firestore query, executes it, and returns a human-readable answer — no SDK required, no engineering bottleneck.
Firebase Analytics tracks events, but connecting those events to user-level Firestore data requires exporting to BigQuery, writing SQL joins, and waiting for pipeline runs. The feedback loop between product behavior and user data is too slow for fast-moving teams.
Query Firebase Analytics and Firestore in the same prompt. Your AI agent joins event data with user properties and Firestore documents in real time — no BigQuery export, no SQL, no pipeline wait.
Teams running separate Firebase staging and production projects need to compare data across environments for debugging and validation. Switching between Firebase console projects, running parallel queries, and manually comparing results wastes hours and introduces errors.
Query both Firebase environments in one prompt. Your AI agent runs parallel queries across projects and returns a side-by-side comparison — instantly, without toggling between console tabs.
Same MCP connection, different workflows for every team member. Agency CEOs get portfolio health. Media Strategists get campaign QA. Analysts get cross-platform reports. Account Managers get auto-generated QBR decks. Creative Directors get performance-based briefs.
Each role asks in natural language. The MCP server handles the complexity — rate limits, auth, schema normalization, governance — behind the scenes.
Firebase MCP is a Model Context Protocol server that connects your Firebase projects — including Firestore, Firebase Analytics, Realtime Database, and Authentication — to AI agents like Claude, ChatGPT, and Gemini. It lets you query and update Firebase data in natural language.
Firestore (read/write documents and collections), Firebase Analytics (events, user properties, funnels), Realtime Database (read/write), Firebase Authentication (user records, sign-in methods), and Remote Config. Coverage depends on your Firebase project configuration.
Both. Read operations cover querying collections, documents, and analytics events. Write operations include creating and updating Firestore documents, modifying user properties, and updating Remote Config parameters. All writes require appropriate service account permissions.
Yes. You can query multiple Firebase projects (e.g., staging and production) in a single prompt. Improvado handles multi-project authentication and returns unified or comparative results.
Yes. Improvado stores Firebase service account credentials in an encrypted vault certified to SOC 2 Type II. The AI model never has direct access to credentials — all requests flow through Improvado's secure proxy.
Under 5 minutes. Add the MCP server URL to your config, upload your Firebase service account JSON through Improvado's credential manager, and start querying. No additional infrastructure required.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
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