Content
# Fabric MCP Server
[![License: MIT][mit_license]][mit_license_link]
[](https://pypi.python.org/pypi/fabric-mcp)
[](https://deepwiki.com/ksylvan/fabric-mcp)
[](https://mseep.ai/app/fca21713-c65c-42ee-b8fa-ce209466e70a)
| main | | | develop | |
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| [![Main Tests][main_tests]][main_tests_link] | [![Main Publish][main_publish]][main_publish_link] | | [![Develop Tests][develop_tests]][develop_tests_link] | [![Develop Publish][develop_publish]][develop_publish_link] |
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Connect the power of the Fabric AI framework to any Model Context Protocol (MCP) compatible application.
This project implements a standalone server that bridges the gap between [Daniel Miessler's Fabric framework][fabricGithubLink] and the [Model Context Protocol (MCP)][MCP]. It allows you to use Fabric's patterns, models, and configurations directly within MCP-enabled environments like IDE extensions or chat interfaces.
Imagine seamlessly using Fabric's specialized prompts for code explanation, refactoring, or creative writing right inside your favorite tools!
## Table of Contents
- [Fabric MCP Server](#fabric-mcp-server)
- [Table of Contents](#table-of-contents)
- [What is this?](#what-is-this)
- [Key Goals \& Features (Based on Design)](#key-goals--features-based-on-design)
- [How it Works](#how-it-works)
- [Project Status](#project-status)
- [Getting Started](#getting-started)
- [Prerequisites](#prerequisites)
- [Installation From Source (for developers)](#installation-from-source-for-developers)
- [Installation From PyPI (for users)](#installation-from-pypi-for-users)
- [Configuration (Environment Variables)](#configuration-environment-variables)
- [Transport Options](#transport-options)
- [Contributing](#contributing)
- [License](#license)
## What is this?
- **Fabric:** An open-source framework for augmenting human capabilities using AI, focusing on prompt engineering and modular AI workflows.
- **MCP:** An open standard protocol enabling AI applications (like IDEs) to securely interact with external tools and data sources (like this server).
- **Fabric MCP Server:** This project acts as an MCP server, translating MCP requests into calls to a running Fabric instance's REST API (`fabric --serve`).
## Key Goals & Features (Based on Design)
- **Seamless Integration:** Use Fabric patterns and capabilities directly within MCP clients without switching context.
- **Enhanced Workflows:** Empower LLMs within IDEs or other tools to leverage Fabric's specialized prompts and user configurations.
- **Standardization:** Adhere to the open MCP standard for AI tool integration.
- **Leverage Fabric Core:** Build upon the existing Fabric CLI and REST API without modifying the core Fabric codebase.
- **Expose Fabric Functionality:** Provide MCP tools to list patterns, get pattern details, run patterns, list models/strategies, and retrieve configuration.
## How it Works
1. An **MCP Host** (e.g., an IDE extension) connects to this **Fabric MCP Server**.
2. The Host discovers available tools (like `fabric_run_pattern`) via MCP's `list_tools()` mechanism.
3. When the user invokes a tool (e.g., asking the IDE's AI assistant to refactor code using a Fabric pattern), the Host sends an MCP request to this server.
4. The **Fabric MCP Server** translates the MCP request into a corresponding REST API call to a running `fabric --serve` instance.
5. The `fabric --serve` instance executes the pattern.
6. The **Fabric MCP Server** receives the response (potentially streaming) from Fabric and translates it back into an MCP response for the Host.
## Project Status
This project is feature-complete.
The project was completed by using the [BMAD-METHOD (Breakthrough Method of Agile Ai-Driven Development)][bmad-method].
The core architecture and proposed tools are outlined in the [High-Level Architecture Document][architecture_doc].
You can also use [](https://deepwiki.com/ksylvan/fabric-mcp) to explore the source code.
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
### Prerequisites
- Python >= 3.10
- [uv](https://github.com/astral-sh/uv) (Python package and environment manager) for developers
### Installation From Source (for developers)
1. **Clone the repository:**
```bash
git clone https://github.com/ksylvan/fabric-mcp.git
cd fabric-mcp
```
2. **Install dependencies using uv sync:**
```bash
uv sync --dev
```
This command ensures your virtual environment matches the dependencies in `pyproject.toml` and `uv.lock`, creating the environment on the first run if necessary.
3. **Activate the virtual environment (uv will create it if needed):**
- On macOS/Linux:
```bash
source .venv/bin/activate
```
- On Windows:
```bash
.venv\Scripts\activate
```
Now you have the development environment set up!
### Installation From PyPI (for users)
If you just want to use the `fabric-mcp` server without developing it, you can install it directly from PyPI:
```bash
# Using pip
pip install fabric-mcp
# Or using uv
uv pip install fabric-mcp
```
This will install the package and its dependencies. You can then run the server using the `fabric-mcp` command.
## Configuration (Environment Variables)
The `fabric-mcp` server can be configured using the following environment variables:
- **`FABRIC_BASE_URL`**: The base URL of the running Fabric REST API server (`fabric --serve`).
- *Default*: `http://127.0.0.1:8080`
- **`FABRIC_API_KEY`**: The API key required to authenticate with the Fabric REST API server, if it's configured to require one.
- *Default*: None (Authentication is not attempted if not set).
- **`FABRIC_MCP_LOG_LEVEL`**: Sets the logging verbosity for the `fabric-mcp` server itself.
- *Options*: `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL` (case-insensitive).
- *Default*: `INFO`
You can set these variables in your shell environment (or put them into a `.env` file in the working directory) before running `fabric-mcp`:
```bash
export FABRIC_BASE_URL="http://your-fabric-host:port"
# This must match the key used by fabric --serve
export FABRIC_API_KEY="your_secret_api_key"
export FABRIC_MCP_LOG_LEVEL="DEBUG"
# Standard I/O transport (default)
fabric-mcp --stdio
# HTTP Streamable transport for HTTP-based MCP clients
fabric-mcp --http-streamable
# Custom host/port for HTTP transport
fabric-mcp --http-streamable --host 0.0.0.0 --port 3000 --mcp-path /message
```
### Transport Options
The `fabric-mcp` server supports multiple transport methods:
- **`--stdio`**: Standard I/O transport for direct MCP client integration (default)
- **`--http-streamable`**: HTTP-based transport that runs a full HTTP server for MCP communication
- `--host`: Server bind address (default: 127.0.0.1)
- `--port`: Server port (default: 8000)
- `--mcp-path`: MCP endpoint path (default: /message)
For more details on transport configuration, see the [Infrastructure and Deployment Overview](./docs/architecture/infrastructure-and-deployment-overview.md#transport-configuration).
## Contributing
Read the [contribution document here](./docs/contributing.md) and please follow the guidelines for this repository.
Also refer to the [cheat-sheet for contributors](./docs/contributing-cheatsheet.md) which contains a micro-summary of the
development workflow.
## License
Copyright (c) 2025, [Kayvan Sylvan](kayvan@sylvan.com) Licensed under the [MIT License](./LICENSE).
[fabricGithubLink]: https://github.com/danielmiessler/fabric
[MCP]: https://modelcontextprotocol.io/
[architecture_doc]: ./docs/architecture/index.md
[develop_publish_link]: https://github.com/ksylvan/fabric-mcp/actions/workflows/publish.yml?branch=develop
[develop_publish]: https://github.com/ksylvan/fabric-mcp/actions/workflows/publish.yml/badge.svg?branch=develop
[develop_tests_link]: https://github.com/ksylvan/fabric-mcp/actions/workflows/tests.yml?branch=develop
[develop_tests]: https://github.com/ksylvan/fabric-mcp/actions/workflows/tests.yml/badge.svg?branch=develop
[mit_license_link]: https://opensource.org/licenses/MIT
[mit_license]: https://img.shields.io/badge/License-MIT-yellow.svg
[main_publish_link]: https://github.com/ksylvan/fabric-mcp/actions/workflows/publish.yml
[main_publish]: https://github.com/ksylvan/fabric-mcp/actions/workflows/publish.yml/badge.svg
[main_tests_link]: https://github.com/ksylvan/fabric-mcp/actions/workflows/tests.yml
[main_tests]: https://github.com/ksylvan/fabric-mcp/actions/workflows/tests.yml/badge.svg
[bmad-method]: https://github.com/bmadcode/BMAD-METHOD
