Peliqan MCP Server

What is the Peliqan MCP Server?

The Peliqan MCP (Model Context Protocol) Server lets AI assistants like Claude.ai, Claude Code, Claude Desktop and ChatGPT talk directly to your Peliqan account. Once connected, the AI can explore your data, debug pipelines, write and run data apps, manage query tables, and call API endpoints — all without leaving your chat. Think of it as giving Claude (or any other MCP Client) a direct line into Peliqan.

Prerequisites

• A Peliqan account
• EU: use mcp.eu.peliqan.io
• US: use mcp.us.peliqan.io
• A Peliqan user (login)
• Claude Code or Claude Desktop installed (or any other MCP Client)

Setup

Setup in ChatGPT

In ChatGPT click on your user name (bottom left corner), in the menu go to Settings > Apps > Create App and enter the Peliqan MCP URL:

Leave the authentication setting to oAuth. Login with your Peliqan user account to authenticate.

Setup in Claude.ai (web) in your Personal account

In Claude.ai in your browser, click on your username (bottom left corner), select Settings from the menu > Connectors > Customize > Click on the plus icon > Select “Add custom connector” and enter the URL of the Peliqan MCP Server:

Login with your Peliqan user account to authenticate.

Setup in Claude.ai (web) in your Organization account

In Claude.ai in your browser, click on your username (bottom left corner), select Organization Settings from the menu > Connectors > Add > Custom > Web, and enter the URL of the Peliqan MCP Server:

Instruct your team members to add a connection using their personal Peliqan account as follows: click on your username (bottom left corner), select Settings from the menu > Connectors > find the Peliqan MCP connection and click on the Connect button:

Setup in Claude Code (terminal)

Run this command:

claude mcp add --transport http peliqan https://mcp.eu.peliqan.io/mcp

Or add the following to your ~/.claude.json file. If the file doesn't exist yet, create it.

{
  "mcpServers": {
    "peliqan": {
      "type": "http",
      "url": "https://mcp.eu.peliqan.io/mcp"
    }
  }
}

After saving, restart Claude Code. You should see Peliqan listed when you type /mcp in the chat.

Setup in Claude Desktop

First, make sure node, npx and mcp-remote are installed on your computer.

For Mac:

• brew install node or visit https://nodejs.org/en/download
• npx mcp-remote

For Windows (PowerShell):

• winget install OpenJS.NodeJS or visit https://nodejs.org/en/download
• npx mcp-remote

Open Claude Desktop settings → Developer → Edit Config and add the below block under mcpServers:

For Mac:

"mcpServers": {
    "peliqan": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.eu.peliqan.io/mcp"
      ]
    }
  }

For Windows:

"mcpServers": {
    "peliqan": {
      "command": "C:\\Progra~1\\nodejs\\npx.cmd",
      "args": [
        "mcp-remote",
        "https://mcp.eu.peliqan.io/mcp"
      ]
    }
  }

If the above configuration on Windows fails with an error “command not found” in the log files of Claude, you can also try one of these values for command:

• "command”: "C:\\\"Program Files\"\\nodejs\\npx.cmd" or
• "command”: "C:/Program Files/nodejs/npx.cmd" or simply
• "command”: "npx.cmd"

Setup in Copilot in Visual Studio (VS Code)

Open mcp.json (or create this file) in the .vscode folder under your Project root in VS Code and add this MCP configuration:

{
  "servers": {
    "peliqan": {
      "type": "http",
      "url": "https://mcp.eu.peliqan.io/mcp"
    }
  }
}

Setup in other MCP Clients

Check your client's documentation on how to add an MCP Server. You can use any MCP-compatible AI client that supports HTTPS transport, and connect using the Peliqan MCP Server URL:

https://mcp.eu.peliqan.io/mcp

Verifying the connection

Once connected, try these prompts to confirm everything is working:

"List my Peliqan connections" "Show me all databases in my Peliqan account” "List my data apps"

If you see results from your Peliqan account, you're all set.

What the Peliqan MCP Server can do

Debug connections & pipelines

• See all your data source connections and their sync status
• View recent pipeline run history
• Read raw error logs when a sync fails

Explore your data

• Browse all databases, schemas, and tables
• Inspect column names and types
• Preview rows of data

Manage query tables

• View run history and error logs for a failing query table
• Check upstream/downstream dependencies before making changes
• Create, update, and delete SQL query tables
• Test fixes in an isolated schema before applying to production

Build & run data apps

• Write Python scripts and run them as background jobs (shell mode)
• Create interactive Streamlit web UIs and publish them with a shareable URL
• Build HTTP API handlers and expose them as REST endpoints
• Schedule scripts to run automatically

Manage API endpoints

• Create, update, and delete HTTP endpoints backed by your Python scripts
• View recent call logs for any endpoint

Sub-account management (partner accounts only)

• List all customer sub-accounts
• Run any tool against a specific sub-account by passing sub_account_id

Resources the AI can read

These are automatically available to the AI — no extra setup needed.

Example prompts to get started

Tips

• The AI reads docs automatically — before writing any Data Apps (Python scripts), tell the AI to read peliqan://docs/data-app-pq first. This ensures it uses the correct pq functions and script structure.
• Deletions are permanent — deleting a schema, table, or data app via the MCP cannot be undone.

Need help?

Reach out to Peliqan support: support@peliqan.io. You can also ask your AI (e.g. Claude) directly. Once the Peliqan MCP Server is connected, the AI has full context on how Peliqan works.