Fastn MCP Server Integration

What does “Fastn” MCP Server do?

The Fastn MCP Server is a scalable platform designed to bridge AI assistants with a wide range of external data sources, APIs, and third-party services. By acting as a unified server, Fastn enables AI-driven workflows to seamlessly connect with platforms like Slack, Notion, HubSpot, and more, facilitating tasks such as real-time API execution, dynamic tool registration, and robust error handling. Its architecture is tailored for high performance and flexibility, making it a valuable asset for developers seeking to enhance the capabilities of AI assistants in environments like Claude, Cursor, and others. Fastn empowers users to automate database queries, manage files, and orchestrate complex API-driven operations, streamlining productivity and enabling more intelligent, context-aware applications.

List of Prompts

No information provided in the repository about prompt templates.

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List of Resources

No information provided in the repository about MCP resources.

List of Tools

No explicit tool list or tool definitions are present in the repository or in fastn-server.py. The server appears to expose API-driven functionality, but specific tool names and descriptions are not listed.

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Use Cases of this MCP Server

• API Integration
  Connects AI assistants with services like Slack, Notion, and HubSpot, enabling streamlined communication, task automation, and workflow orchestration.
• Real-time Operations
  Executes API-driven tasks on-the-fly, supporting dynamic interaction between AI agents and external platforms.
• Automated Workspace Management
  Facilitates workspace setup and administration via API, simplifying onboarding and management processes.
• Enhanced Logging and Error Handling
  Provides robust logging and error management, making it easier for developers to monitor, debug, and maintain AI-driven workflows.

How to set it up

Windsurf

1. Ensure Python 3.10+ is installed.
2. Install the Fastn MCP Server:
   pip install fastn-mcp-server
3. Obtain your API key and Workspace ID from your Fastn account.
4. Configure the MCP Server in Windsurf’s configuration file:

   {
       "mcpServers": {
           "fastn": {
               "command": "/path/to/fastn-mcp-server",
               "args": [
                   "--api_key",
                   "YOUR_API_KEY",
                   "--space_id",
                   "YOUR_WORKSPACE_ID"
               ]
           }
       }
   }
   

5. Save changes and restart Windsurf. Verify the MCP server is running.

Claude

1. Find the path to the installed fastn-server (macOS/Linux: which fastn-server).
2. Open the Claude configuration file:
   ~/Library/Application Support/Claude/claude_desktop_config.json
3. Add the MCP server configuration:

   {
       "mcpServers": {
           "fastn": {
               "command": "/path/to/your/uv",
               "args": [
                   "--directory",
                   "/path/to/your/fastn-server",
                   "run",
                   "fastn-server.py",
                   "--api_key",
                   "YOUR_API_KEY",
                   "--space_id",
                   "YOUR_WORKSPACE_ID"
               ]
           }
       }
   }
   

4. Save and restart Claude. Confirm the MCP server is available.

Cursor

1. Open Cursor settings.
2. Navigate to the “MCP” section and click “Add New”.
3. Name your server (e.g., “fastn”) and select “Command” as the type.
4. Enter the following configuration:

   {
       "mcpServers": {
           "fastn": {
               "command": "/path/to/fastn-mcp-server",
               "args": [
                   "--api_key",
                   "YOUR_API_KEY",
                   "--space_id",
                   "YOUR_WORKSPACE_ID"
               ]
           }
       }
   }
   

5. Save and restart Cursor.

Cline

No specific setup instructions provided for Cline.

Securing API Keys

Use environment variables for sensitive information.
Example:

{
    "mcpServers": {
        "fastn": {
            "env": {
                "FASTN_API_KEY": "your_api_key",
                "FASTN_SPACE_ID": "your_space_id"
            },
            "inputs": {
                "api_key": "${FASTN_API_KEY}",
                "space_id": "${FASTN_SPACE_ID}"
            }
        }
    }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "fastn": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “fastn” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Rating paragraph:
The Fastn MCP server provides solid documentation for setup and general API integration, but lacks detailed information about available prompts, resources, and tools, which may hinder quick adoption for some users. Its support for key platforms and secure credential management is a plus, but the absence of sampling and roots support (based on available documentation) keeps its overall composability limited.

MCP Score