> For the complete documentation index, see [llms.txt](https://docs.k3-labs.com/introduction/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.k3-labs.com/introduction/ai-automation-suite/mcp-server/available-mcp-integrations.md).

# Available MCP Integrations

K3 Labs supports two categories of MCP integrations: pre-built integrations for popular services and custom MCP server connections for any service supporting the MCP standard.

### Available MCP Integrations

<table><thead><tr><th>MCP Name</th><th width="119.7664794921875">Category</th><th>Description</th><th>Use Cases</th></tr></thead><tbody><tr><td><strong>Custom MCP Server</strong></td><td>Universal</td><td>Connect any MCP-compatible service via SSE endpoint</td><td>API integrations, Custom tools, Third-party services</td></tr><tr><td><strong>PostgreSQL MCP</strong></td><td>Database</td><td>Direct PostgreSQL database access and SQL execution</td><td>Database queries, Data analysis, Report generation</td></tr><tr><td><strong>CoinGecko MCP</strong></td><td>Crypto Data</td><td>Real-time cryptocurrency market data and analysis</td><td>Price tracking, Market analysis, Portfolio monitoring</td></tr></tbody></table>

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### Using MCP Tools in Workflows

After configuring your MCP integrations, they become available in AI Agent functions:

1. **Create or Edit AI Agent**: Add an AI Agent function to your workflow
2. **Select Tool**: In the Tool dropdown, choose your configured MCP integration
3. **Configure AI Agent**: The AI will automatically use the selected MCP tool based on user prompts and conversation context
4. **Deploy**: Deploy your workflow to start using the MCP-powered AI Agent

The AI Agent will intelligently decide when to call your MCP tools based on user requests, making complex integrations accessible through natural language conversations.