Fabric MCP Server

What is Fabric MCP Server about?

Fabric MCP Server makes the extensive collection of Fabric patterns available as individual tools that can be invoked by MCP‑compatible AI agents. By turning each pattern into a callable tool, the server lets AI assistants perform complex prompt‑engineering, analysis, and content‑generation workflows without leaving the chat environment.

How to use Fabric MCP Server?

1. Install – Clone the repository, run npm install, and build with npm run build.
2. Start the server – Execute the built entry point (e.g., node build/index.js) or use the supplied MCP configuration in your AI agent.
3. Configure your AI tool – Add a server entry to the MCP settings of Claude Desktop, VS Code +Cline, or any other MCP‑compatible assistant.
4. Select a pattern – Within a conversation, request a specific Fabric pattern (e.g., summarize, extract_wisdom). The assistant will call the corresponding tool on the server and return the result.

Key Features of Fabric MCP Server

• Full pattern catalog – Every Fabric pattern is exposed as a separate tool.
• Cross‑platform – Works with Claude Desktop, Cline, and any MCP‑compatible agent.
• Simple installation – Standard Node.js workflow (clone, npm install, build).
• Extensible – New patterns added to the Fabric repository become instantly available.
• Tool‑driven AI augmentation – Enables AI assistants to perform concrete actions (analysis, visualization, summarization) through pattern execution.

Use Cases of Fabric MCP Server

• Code review assistance – Invoke analyze_claims to automatically evaluate code change claims.
• Knowledge extraction – Use extract_wisdom to pull key insights from long documents.
• Visualization generation – Call create_mermaid_visualization to produce diagram text for Mermaid.
• Rapid summarization – Deploy summarize for concise overviews of articles, tickets, or specifications.
• Custom workflow automation – Chain multiple patterns to build complex multi‑step AI workflows.

FAQ

Q: Do I need a special runtime to run the server?\nA: Only Node.js (>=14) is required; the project is pure TypeScript compiled to JavaScript.

Q: Can I use the server with other AI platforms?\nA: Yes. Any AI assistant that supports the Model Context Protocol can consume the tools after adding the appropriate MCP configuration.

Q: How are new Fabric patterns added?\nA: Adding a new pattern to the Fabric repository automatically makes it available; no code changes in the server are needed.

Q: What if the server fails to start?\nA: Verify that npm install completed without errors, that the build/index.js file exists, and that Node.js is on your PATH. Check console output for error details.

fabric-mcp-server

Table of Contents

1. Introduction
2. What is Model Context Protocol (MCP)?
3. Features
4. Tools
5. Installation
6. Usage
7. Configuration for Claude Desktop
8. Configuration for VS Code with Cline
9. Tips for Using with Different AI Agents
10. Troubleshooting
11. Contributing
12. License

Introduction

The fabric-mcp-server is a Model Context Protocol (MCP) server designed to expose Daniel Miessler's Fabric patterns as tools for integration with AI coding agents and assistants. This integration enhances AI capabilities by leveraging AI-driven pattern execution from the Fabric repository. The server works with various AI platforms including Claude Desktop, Cline, and other MCP-compatible AI agents.

What is Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is a specification that facilitates communication between AI systems and external tools or resources. It standardizes the way AI models interact with various capabilities such as databases, APIs, and file systems. MCP servers, like fabric-mcp-server, implement this protocol to make tools and resources accessible to AI models, thereby expanding their functional scope.

Features

• Exposes Fabric Patterns as Tools: The server makes all Fabric patterns available as individual tools within MCP-compatible AI agents.
• Pattern Execution: Users can select and execute Fabric patterns directly within AI assistant tasks.
• Enhanced Capabilities: Integrates AI-driven pattern execution to augment AI assistant functionality.
• Cross-Platform Compatibility: Works with Claude Desktop, Cline, and other MCP-compatible AI agents.

Tools

The fabric-mcp-server exposes a wide range of Fabric patterns as tools. Some examples include:

• analyze_claims
• summarize
• extract_wisdom
• create_mermaid_visualization
• And many more...

To see the full list of available patterns, you can list the directories in the [fabric/patterns](https://github.com/danielmiessler/Fabric/tree/main/data/patterns) directory.

Installation

1. Clone the Repository: Clone the fabric-mcp-server repository to your local system.
2. Install Dependencies: Navigate into the fabric-mcp-server directory and run npm install.
3. Build the Project: Run npm run build to compile the TypeScript code.

Usage

To use the fabric-mcp-server with AI agents:

1. Ensure the server is installed and running.
2. Configure the MCP server in your AI agent's settings file.
3. Create a new task or conversation and select a Fabric pattern to use.

The specific configuration steps vary depending on which AI agent you're using. See the sections below for detailed instructions.

Configuration for Claude Desktop

To use fabric-mcp-server with Claude Desktop:

1. Complete Installation: Follow the installation steps above to build the project.

2. Configure Claude Desktop: Add the MCP server configuration to your Claude Desktop settings. The configuration file is typically located at:

   • Windows: %APPDATA%\Claude\claude_desktop_config.json
   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Linux: ~/.config/Claude/claude_desktop_config.json

3. Add Server Configuration: Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "fabric-mcp-server": {
      "command": "node",
      "args": [
        "<path-to-fabric-mcp-server>/build/index.js"
      ],
      "env": {}
    }
  }
}

Replace <path-to-fabric-mcp-server> with the actual path to the fabric-mcp-server directory on your system.

4. Restart Claude Desktop: Restart Claude Desktop to apply the changes.

Configuration for VS Code with Cline

To use fabric-mcp-server with Cline in VS Code:

1. Complete Installation: Follow the installation steps above to build the project.

2. Configure Cline Settings: Add the MCP server configuration to your Cline settings file. The file path varies by operating system:

   • Windows: C:\Users\<username>\AppData\Roaming\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
   • macOS: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
   • Linux: ~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

3. Add Server Configuration: Use the following configuration:

{
  "fabric-mcp-server": {
    "command": "node",
    "args": [
      "<path-to-fabric-mcp-server>/build/index.js"
    ],
    "env": {},
    "disabled": false,
    "autoApprove": [],
    "transportType": "stdio",
    "timeout": 60
  }
}

Replace <path-to-fabric-mcp-server> with the actual path to the fabric-mcp-server directory on your system. For example:

• Windows: "C:\\path\\to\\fabric-mcp-server\\build\\index.js"
• macOS/Linux: "/path/to/fabric-mcp-server/build/index.js"

4. Restart VS Code: Restart VS Code or reload the Cline extension to apply the changes.

Tips for Using with Different AI Agents

For Claude Desktop Users

• Simply mention that you'd like to use a Fabric pattern in your conversation
• Ask Claude to list available patterns if you're unsure which one to use
• The patterns will be automatically available as tools once configured

For Cline Users

To maximize the benefits of fabric-mcp-server with Cline, add use fabric-mcp-server at the end of your prompts or consider adding the following rule to your .clinerules file:

# Fabric MCP Server Rule
1. **List Fabric Patterns**: When a new task is created, list all pattern names from the Fabric repository.
2. **Prompt for Pattern Selection**: Ask the user to select one of the following options:
   a) Enter a pattern name from the list to use the `fabric-mcp-server` tool with the specified pattern.
   b) Choose not to use `fabric-mcp-server` for the task.

This rule streamlines the tool selection process for new tasks in Cline.

For Other MCP-Compatible Agents

• Consult your specific AI agent's documentation for MCP server configuration
• The basic server configuration should be similar to the examples above
• Ensure your agent supports the MCP protocol and tool execution

Troubleshooting

• Ensure the fabric-mcp-server is correctly configured in your AI agent's settings.
• Verify that the server is running and reachable.
• Check the console output for any error messages.
• Make sure the path to the build/index.js file is correct and accessible.
• Verify that Node.js is installed and available in your system PATH.

Contributing

Contributions to fabric-mcp-server are welcome. Please refer to the CONTRIBUTING.md file for guidelines on how to contribute.

License

fabric-mcp-server is released under the MIT License.