# Fauna (Serverless DB) MCP for AI Agents AI Agent Connect > Fauna (Serverless DB) MCP lets you run FQL queries and manage your serverless database directly through your AI client. You can list collections, query indexes, and fetch documents without leaving your editor. It turns your AI into a database administrator that understands your specific schema and data structure. ## Overview - **Category:** developer-tools - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_hEG5bwdrY3FdPx62RCPAMcIqUBDzab1jcyYhjY8I/ai-agent-connect - **Tags:** fauna, fql, serverless-database, nosql, database-management ## Description This database MCP lets you talk to your serverless database through your AI client. You can stop jumping between your code editor and a separate dashboard just to check if a record landed or to see what a specific index looks like. Instead of manually crafting complex query strings in a different tab, you just tell your agent what data you need. It handles the heavy lifting of turning your request into a valid command. You can explore your collections, grab specific documents, or verify that a migration went through without losing your flow. It is part of the Vinkius catalog, so it plugs right into your existing setup. If you need to see a list of users or check a specific log entry, you just ask. It acts like a database administrator who knows your schema inside out. You save time on the quick checks and spend more time actually building features. You can also use it to manage your schema or check how your indexes are performing. It removes the friction of having to remember specific syntax for every single operation. When you are debugging a production issue, you can ask for the last few entries in a log collection to see exactly what happened. This makes it much easier to spot errors quickly. You can also use it to perform bulk updates or deletions by describing the criteria in plain English. It gives you a way to interact with your data that feels like a conversation rather than a series of manual commands. It is built to handle your specific database structure, making it a reliable way to manage your data infrastructure without the constant context switching. ## Tools ### execute_fql Run complex Fauna Query Language commands to modify or read your data. It handles the logic of your database requests based on the query string you provide. ## Prompt Examples **Prompt:** ``` Find a user document where the email is 'dev@example.com'. ``` **Response:** ``` I've searched your users collection for that email. Here is the record I found: | ID | Email | Name | Status | | :--- | :--- | :--- | :--- | | 3849201 | dev@example.com | Dev User | Active | Would you like me to update any details on this account? ``` **Prompt:** ``` Create a new entry in the 'Logs' collection with the message 'System started'. ``` **Response:** ``` I've successfully added that entry to your logs. **Log Entry Created:** - **Message:** System started - **Timestamp:** 2026-07-10T15:44:31Z - **Status:** Success ``` **Prompt:** ``` List all documents in the 'Products' collection using FQL. ``` **Response:** ``` I've fetched all documents from your Products collection. Here are the current items: - **Product A**: $49.99 (In Stock) - **Product B**: $29.99 (Out of Stock) - **Product C**: $15.00 (In Stock) Let me know if you need to see more details on any of these. ``` ## Capabilities ### Run FQL queries Execute commands to read, create, update, or delete data in your database. ### List collections See all the different data groups within your serverless database. ### Query indexes Find specific records faster by searching through your defined indexes. ### Fetch documents Retrieve individual records using their unique identifiers. ### Inspect schema View the structure of your collections and how they are linked together. ### Pass JSON data Send complex data objects into your queries using a safe arguments field. ## Use Cases ### Verifying a user sign up A developer needs to check if a new registration hit the database. They ask the agent to find the user by email and confirm the record exists. ### Cleaning up old logs A data engineer needs to remove entries older than 30 days. They ask the agent to delete those records using a natural language prompt. ### Checking recent orders A product manager wants to see the last 10 orders. They ask the agent to list the most recent entries in the Orders collection. ### Testing new features A backend dev is testing a new feature and uses the agent to create a dummy user to verify that permissions are working correctly. ## Benefits - Stop context switching by running execute_fql directly in your IDE or chat. You don't have to leave your workspace to verify data. - Speed up debugging by asking your agent to fetch specific documents or list records instantly. It removes the friction of manual querying. - Simplify schema management by letting your AI client inspect your collections and indexes. You can see how your data is structured in seconds. - Execute complex data migrations more safely by using parameterized queries. Your agent can handle the JSON mapping while you focus on the logic. - Get real-time data insights for your product team without building custom admin panels. Just ask the agent to pull the latest metrics for you. ## How It Works The bottom line is you get a direct line to your data without leaving your primary workspace. 1. Subscribe to the Connector and provide your Fauna Secret and Region URL. 2. Connect the Connector to your AI client like Claude or Cursor. 3. Ask your agent to perform tasks like finding a user or listing recent logs. ## Frequently Asked Questions **Can the Fauna (Serverless DB) MCP help me run queries?** Yes, it lets your agent execute FQL commands to read, update, or delete data in your database using natural language. **Do I need to keep the Fauna dashboard open while using this Connector?** No, you can do almost everything through your AI client, which saves you from having to keep multiple tabs open. **Is it safe to use the Fauna (Serverless DB) MCP for data deletions?** Yes, it's safe as long as you double-check the queries your agent generates before confirming the action. **Can I use the Fauna (Serverless DB) MCP with Cursor?** Yes, it works perfectly with Cursor, Claude, and any other MCP-compatible client. **Does the Fauna (Serverless DB) MCP support my specific region?** Yes, you just need to provide your Region URL during the initial setup process. **Can I manage my database schema with the Fauna (Serverless DB) MCP?** Yes, it can inspect and manage your collections and indexes using standard FQL commands. **Can I perform write operations like creating or updating documents?** Yes. The `execute_fql` tool allows any valid FQL command. If your Fauna Secret has the appropriate permissions (e.g., 'server' or 'admin' role), you can create, update, and delete data. **How do I handle complex query arguments?** You can use the optional `arguments` parameter in the `execute_fql` tool. Pass a JSON object containing your variables, and reference them within your FQL string. **Does this support Fauna's regional endpoints?** Yes. You can provide a `FAUNA_REGION_URL` (e.g., for US or EU regions) as an optional credential during setup to ensure the agent connects to the correct database cluster.