Model Context Protocol (MCP)

What is MCP?

MCP (Model Context Protocol) (opens in a new tab) is an open protocol, initiated by Anthropic, that standardizes how AI agents connect with external data, tools, and services.

Think of it like a USB-C port for your AI agent. Normally, connecting an AI agent to external tools (like reading data from Google Drive or triggering actions in other apps) requires complex, time-consuming setup, especially if you're not a technical expert.

MCP simplifies this dramatically. Different providers offer MCP servers, which act like USB-C hubs packed with specific data or tools. You can "plug" one of these servers into your MindPal agent using just a single URL. Instantly, your agent gains access to everything offered by that server – no complicated configuration needed.

Why use MCP?

MCP offers several key benefits:

• Simple Integration: Connect your AI agents to external tools with just a URL, eliminating complex coding or setup.
• Enhanced Capabilities: Give your agents access to a much wider range of data and functionality from external sources.
• Streamlined Workflows: Build more powerful and efficient automated processes by letting agents interact with other apps and services.
• Better Context: Allow agents to understand and work with your specific data and tools more effectively.

Given MCP's transformative potential, MindPal proudly leads as the first no-code AI agent platform to integrate this technology, democratizing access to these advanced capabilities for all users.

MCP Support in MindPal

It's important to know what MindPal currently supports regarding MCP:

• Tools Only: An MCP server can potentially offer various things like Resources, Prompts, or Sampling Routes. Right now, MindPal only supports Tools provided by MCP servers.
• Streamable HTTP/SSE Servers Only: MCP servers can operate in different ways. MindPal supports Streamable HTTP and SSE (Server-Sent Events) servers, which are suitable for cloud-based applications like ours. We do not support STDIO servers, which are typically used for local integrations.

How to configure MCP in MindPal

Setting up an MCP connection in MindPal is straightforward:

1. Find a remote MCP Server: Locate a server that provides the tools your agent needs. See the list below for some compatible options.
2. Navigate to Agent Settings: Go to the settings page for the AI agent you want to configure.
3. Go to the MCP Section: Find the section dedicated to MCP connections.
4. Add Server: Click on "Add new remote MCP server".
5. Enter Details: Paste your MCP server URL and give the connection a recognizable name.
6. Save & Test: Save the configuration. MindPal will automatically test the connection to verify that the server is reachable and configured correctly, and to retrieve the list of available tools.

That's it! Your AI agent is now ready to use the tools provided by the connected MCP server. It really just takes a URL.

Proven Compatible MCP Servers

Below are some of the most popular and proven compatible remote MCP servers you can use with MindPal. Each offers unique capabilities and setup flows. Pick the one that fits your workflow best.

Zapier MCP (opens in a new tab)

• Offers: Access to 7,000+ apps with fine-grained control over individual actions
• Access: Sign up, create your MCP server, add desired actions, use your unique server URL

Make MCP (opens in a new tab)

• Offers: Turn existing "On Demand" Make Scenarios into tools for AI with bidirectional communication
• Access: Create account, set up Scenarios as "On Demand," generate MCP token in Profile page

Composio MCP (opens in a new tab)

• Offers: Multiple server endpoints, each connecting to specific applications with built-in authentication
• Access: Create an account, select the applications you want to connect, and receive dedicated MCP server URLs for each integration

Activepieces MCP (opens in a new tab)

• Offers: Turn "Pieces" (single actions) and "Flows" (multi-step workflows) into MCP tools, with configurable inputs and outputs for MCP tools
• Access: Use their cloud service or self-host. Go to AI → MCP in your Activepieces Dashboard, start connecting the tools that you want to give AI access to, use your unique server URL

Pipedream MCP (opens in a new tab)

• Offers: Access to 2,500+ APIs and 10,000+ integration tools, with dedicated endpoints for each connected service
• Access: Create an account, choose your desired integrations, and receive a unique server URL for each of your integrations

n8n MCP Server (opens in a new tab)

• Offers: Turns n8n workflows into MCP tools, allowing AI applications to access n8n's automation capabilities and integration with hundreds of services
• Access: Set up the MCP Server Trigger node in your n8n workflow, configure authentication, and use the generated MCP URL to connect

Supermachine Public MCP Servers (opens in a new tab)

• Offers: Access to 3939+ public MCP servers by spinning up virtual machines that run these MCP servers with minimal configuration
• Access: Search and spin up remote MCPs through the Supermachine platform, then use them in your AI applications

Smithery (opens in a new tab)

• Offers: Access to 7,316+ MCP servers built by the community, including web search, memory management, browser automation, third-party tool integrations, database query integration, and weather data APIs
• Access: Create an account and access the platform's extensive library of community-built skills and extensions

Pabbly Connect MCP (opens in a new tab)

• Offers: Seamless workflow automation and AI tool integration with direct access to Pabbly Connect's suite of business management applications (including CRM, email, billing, forms, and more) via MCP. Enables AI assistants to execute workflow actions, add leads, send emails, fetch data, and more, directly from your Pabbly Connect workflows.
• Access: In your Pabbly Connect workflow, use the "Add to MCP server" option for any action, configure your tool, and retrieve your unique MCP Server URL from Pabbly Connect MCP Settings (opens in a new tab). Use this URL as your endpoint for AI clients (e.g., Claude Desktop, etc). See setup instructions (opens in a new tab) for full details.

DeepWiki MCP (opens in a new tab)

• Offers: Access to GitHub repository documentation and AI-powered search capabilities. Includes tools to read wiki structure, view documentation contents, and ask questions about repositories
• Access: Free, remote, no-authentication-required service. Server URLs: https://mcp.deepwiki.com/sse (SSE) or https://mcp.deepwiki.com/mcp (Streamable HTTP)

GitMCP (opens in a new tab)

• Offers: Instant MCP server creation for any GitHub repository by simply changing the domain from github.com to gitmcp.io. Provides AI assistants with deep code context including llms.txt, llms-full.txt, readme.md and more
• Access: No setup required. Simply replace github.com with gitmcp.io in any repository URL to get an instant MCP server endpoint

Supermemory MCP (opens in a new tab)

• Offers: Personal, universal memory layer that travels with you across different AI platforms. Store and retrieve memories, create a persistent knowledge base
• Access: Get your unique MCP URL (keep secret) on the website

Apify Actors MCP (opens in a new tab)

• Offers: Access to 4,000+ web scraping and automation tools
• Access: Server available at https://mcp.apify.com (streamable) or https://mcp.apify.com/sse (SSE transport) with Authorization: Bearer <APIFY_TOKEN> header. Get your API token from Apify Console Integrations section

Firecrawl MCP (opens in a new tab)

• Offers: Web scraping, crawling, and discovery with advanced content extraction, search capabilities, deep research, and structured data extraction using LLM
• Access: Server available at https://mcp.firecrawl.dev/{FIRECRAWL_API_KEY}/sse with API key authentication required. Get your API key from firecrawl.dev/app/api-keys (opens in a new tab)

We will continuously test and add more compatible MCP servers to this list as they become available.

Learn more about MCP

For a deeper understanding of MCP and its potential, check out Anthropic's resources or our blog post: Model Context Protocol Explained: AI for Everyone (opens in a new tab)