Why these MCP servers
Data MCP servers let an AI agent inspect a schema, run a query, and summarize a result set. Postgres, MongoDB, and Redis are the most common starting points. Supabase MCP adds managed Postgres, auth, and storage. Stripe MCP exposes billing context. The pattern is the same: connect the agent to a read-only database user, give it the schema, and let it ask questions.
Recommended MCP servers
A curated shortlist of the most useful MCP servers for this workflow.
Postgres MCP
Query relational data from agent workflows
Connect AI agents to PostgreSQL with schema inspection, read-only query controls, and concise table context for safer database exploration. The reference implementation also supports restricted write access for migrations.
MongoDB MCP
Document database access for agents
Query MongoDB collections, run aggregations, and inspect schema through MCP. A practical fit for content platforms, catalogs, and any document-shaped data product.
Redis MCP
Cache, queues, and pub/sub for agents
Read and write Redis keys, manage TTLs, and publish events from MCP clients. Useful for agents that need ephemeral state, rate limiting, or queue coordination.
SQLite MCP
Local-first SQL for agents
Query local SQLite databases through MCP. A lightweight option for desktop tools, browser extensions, and any agent that needs a zero-setup SQL backend.
Supabase MCP
Postgres, auth, and edge functions for agents
The official Supabase MCP server exposes database, auth, storage, and edge function tools. Read-only by default with optional write access for migrations and schema introspection.
Stripe MCP
Customers, invoices, and payments for agents
Expose Stripe customers, invoices, subscriptions, and payment intents to MCP clients with strict, auditable scopes. Perfect for support agents that need billing context without opening the dashboard.
Fetch MCP
HTTP requests with model-friendly output
A simple HTTP fetch MCP server that returns cleaned-up HTML, Markdown, or JSON. It is the recommended tool for agents that need to read a page without a full browser stack.
Memory MCP
Persistent knowledge graph for agents
A knowledge-graph based memory layer that lets agents remember entities, relationships, and observations across sessions. The canonical implementation uses a local JSON store for zero-config persistence.
How to set this up
- 1
Create a read-only database user
Most MCP servers default to read-only, but you can enforce this at the database level by creating a dedicated user with read-only grants.
- 2
Install Postgres MCP
The reference implementation in modelcontextprotocol/servers works with any Postgres-compatible database. For Snowflake or BigQuery, check the community for a dedicated server.
- 3
Add Supabase MCP (if you use Supabase)
Supabase MCP exposes your database, auth users, and storage in a single server.
- 4
Add Stripe MCP for revenue context
Stripe MCP lets the agent pull customer, invoice, and subscription data into the conversation.
- 5
Add Memory MCP for context
Memory MCP gives the agent a persistent knowledge graph so it can remember findings across sessions.
Frequently asked questions
Is it safe to let an AI agent query my warehouse?
Yes, if you use a read-only database user with row-level security and a query timeout. Most data MCP servers support a read-only mode that you can enforce at the connection level.
Can an MCP server run dbt?
Not directly, but you can use the Filesystem MCP server to read dbt project files and the Postgres MCP server to query the resulting models. Some teams wrap dbt in a custom MCP server.