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Build your own PostgreSQL MCP server

JimleukJimleuk
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2/3/2026
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This n8n demonstrates how to build a simple PostgreSQL MCP server to manage your PostgreSQL database such as HR, Payroll, Sale, Inventory and More!

This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/postgres

How it works

  • A MCP server trigger is used and connected to 5 tools: 2 postgreSQL and 3 custom workflow.
  • The 2 postgreSQL tools are simple read-only queries and as such, the postgreSQL tool can be simply used.
  • The 3 custom workflow tools are used for select, insert and update queries as these are operations which require a bit more discretion.
  • Whilst it may be easier to allow the agent to use raw SQL queries, we may find it a little safer to just allow for the parameters instead. The custom workflow tool allows us to define this restricted schema for tool input which we'll use to construct the SQL statement ourselves.
  • All 3 custom workflow tools trigger the same "Execute workflow" trigger in this very template which has a switch to route the operation to the correct handler.
  • Finally, we use our standard PostgreSQL node to handle select, insert and update operations. The responses are then sent back to the the MCP client.

How to use

  • This PostgreSQL MCP server allows any compatible MCP client to manage a PostgreSQL database by supporting select, create and update operations. You will need to have a database available before you can use this server.
  • Connect your MCP client by following the n8n guidelines here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/#integrating-with-claude-desktop
  • Try the following queries in your MCP client:
    • "Please help me check if Alex has an entry in the users table. If not, please help me create a record for her."
    • "What was the top selling product in the last week?"
    • "How many high priority support tickets are still open this morning?"

Requirements

  • PostgreSQL for database. This can be an external database such as Supabase or one you can host internally.
  • MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download

Customising this workflow

  • If the scope of schemas or tables is too open, try restrict it so the MCP serves a specific purpose for business operations. eg. Confine the querying and editing to HR only tables before providing access to people in that department.
  • Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

n8n PostgreSQL MCP Server

This n8n workflow acts as a Model Context Protocol (MCP) server, allowing AI models to interact with a PostgreSQL database. It provides a structured way for AI agents to query and potentially manipulate data within a PostgreSQL instance, acting as a specialized tool for database operations.

What it does

This workflow simplifies the integration of AI models with PostgreSQL by:

  1. Listening for MCP Server Requests: It acts as an MCP server, waiting for incoming requests from AI models or other systems that adhere to the Model Context Protocol.
  2. Executing PostgreSQL Operations: Upon receiving a request, it uses the PostgreSQL node to perform database operations. The specific operation (e.g., query, insert, update) would be determined by the incoming MCP request.
  3. Routing Logic (Implicit): Although not explicitly configured with multiple branches in the provided JSON, the presence of a Switch node suggests that future enhancements could involve routing different types of MCP requests to various PostgreSQL operations or other actions.
  4. Calling Sub-Workflows (Implicit): The Call n8n Workflow Tool node indicates that this workflow can potentially delegate complex tasks to other n8n workflows, extending its capabilities beyond direct database interaction.
  5. Triggering Other Workflows (Implicit): The When Executed by Another Workflow node suggests it can also be invoked as a sub-workflow by a parent workflow, enabling modular and reusable AI tools.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance to import and execute the workflow.
  • PostgreSQL Database: Access to a PostgreSQL database instance.
  • PostgreSQL Credentials: Configured n8n credentials for connecting to your PostgreSQL database.
  • Model Context Protocol (MCP) Client: An AI model or application capable of sending requests formatted according to the Model Context Protocol to this n8n workflow's webhook URL.

Setup/Usage

  1. Import the Workflow:
    • Copy the provided JSON code.
    • In your n8n instance, go to "Workflows" and click "New".
    • Click the three dots next to the workflow name and select "Import from JSON".
    • Paste the JSON code and click "Import".
  2. Configure PostgreSQL Credentials:
    • Locate the "Postgres" node.
    • Click on the "Credential" field and select an existing PostgreSQL credential or create a new one.
    • Enter your PostgreSQL database connection details (host, port, database, user, password).
  3. Activate the MCP Server Trigger:
    • Locate the "MCP Server Trigger" node.
    • Save and activate the workflow. This will expose a webhook URL that your MCP client can use to send requests.
  4. Integrate with your AI Model:
    • Configure your AI model or MCP client to send requests to the webhook URL provided by the "MCP Server Trigger" node. The requests should adhere to the Model Context Protocol specification for PostgreSQL operations.
    • The workflow will then process these requests, interact with the PostgreSQL database, and return a response to the MCP client.
  5. Optional: Configure Switch and Call Workflow Tool:
    • If you plan to extend the workflow's logic, configure the "Switch" node to route different types of MCP requests to specific branches.
    • Utilize the "Call n8n Workflow Tool" node to integrate other n8n workflows as sub-tools for more complex operations.

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