https://github.com/composable-delivery/snowfakery-mcp
MCP Server for Snowfakery data generation
https://github.com/composable-delivery/snowfakery-mcp
Last synced: 5 months ago
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MCP Server for Snowfakery data generation
- Host: GitHub
- URL: https://github.com/composable-delivery/snowfakery-mcp
- Owner: composable-delivery
- License: apache-2.0
- Created: 2026-01-12T17:29:59.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2026-01-16T16:18:25.000Z (5 months ago)
- Last Synced: 2026-01-17T02:23:06.598Z (5 months ago)
- Language: Python
- Size: 1.19 MB
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE-APACHE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
- Copyright: COPYRIGHT
Awesome Lists containing this project
- awesome-mcp-security - snowfakery-mcp - githubcom-composable-delivery-snowfakery-mcp) | (γ«γγ΄γͺ / π οΈ <a name="developer-tools"></a>ιηΊγγΌγ«)
README
# Snowfakery MCP Server
[](https://github.com/composable-delivery/snowfakery-mcp/actions/workflows/ci.yml)
[](https://github.com/composable-delivery/snowfakery-mcp/actions/workflows/release.yml)
[](https://pypi.org/project/snowfakery-mcp/)
[](https://codecov.io/gh/composable-delivery/snowfakery-mcp)
[](LICENSE-MIT)
**Power up your AI workflows with Snowfakery data generation** β Use Claude, ChatGPT, and other AI assistants to author, debug, and run data recipes through the [Model Context Protocol](https://modelcontextprotocol.io/).
## MCP Registry
mcp-name: io.github.composable-delivery/snowfakery-mcp
## What is this?
[Snowfakery](https://github.com/SFDO-Tooling/Snowfakery) is a YAML-based tool for programmatically generating test data. This MCP server connects Snowfakery to AI assistants, letting you:
- **Draft recipes** with AI assistance backed by real Snowfakery docs and examples
- **Validate recipes** before running them with detailed error feedback
- **Execute recipes** and iterate on results interactively
- **Debug issues** with static analysis and recipe inspection
- **Generate Salesforce mappings** for CumulusCI workflows
Perfect for teams that need realistic test dataβfrom Salesforce admins to developers building data pipelines.
## Quick Start
### Install `uv`
We recommend using `uv` for installs and for running from source.
- Install `uv` (macOS/Linux):
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
- Install `uv` (Windows PowerShell):
```powershell
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
```
See the official `uv` install docs:
### Claude Desktop (recommended)
For Claude Desktop, prefer using the `.mcpb` bundle from Releases:
- Download the latest `.mcpb` from
- Add the bundle in Claude Desktop as an MCP server bundle
This bundle includes the pinned runtime metadata (`uv.lock`, `manifest.json`) and is the easiest way to get a reproducible setup.
### Install & Run (CLI)
```bash
# Recommended: isolated install
uv tool install snowfakery-mcp
# Then run the server
snowfakery-mcp
```
Or from source:
```bash
git clone https://github.com/composable-delivery/snowfakery-mcp.git
cd snowfakery-mcp
uv sync
uv run snowfakery-mcp
```
### Connect to Claude (Desktop)
Add to your Claude Desktop `claude_desktop_config.json`:
```json
{
"mcpServers": {
"snowfakery-mcp": {
"command": "snowfakery-mcp"
}
}
}
```
Then ask Claude:
> "Show me an example Snowfakery recipe" or "Help me write a recipe to generate 100 Salesforce accounts"
## Features
**Resources** β Access docs, examples, and schemas:
- Snowfakery documentation and recipe examples
- JSON schema for recipe validation
- Run outputs and artifacts
**Tools** β Interact with recipes:
- Validate & analyze recipes (catch errors early)
- Run recipes and capture output
- List & retrieve example recipes
- Generate CumulusCI mapping files
## Learn More
- **[MCP_SERVER_SPEC.md](MCP_SERVER_SPEC.md)** β detailed design and tool catalog
- **[Snowfakery docs](https://snowfakery.readthedocs.io/)** β recipe language reference
- **[Contributing](CONTRIBUTING.md)** β how to contribute
## Community
We want this to be welcoming at any level. Questions, ideas, and contributions are always welcome!
- **Questions & ideas?** Open a [GitHub Discussion](https://github.com/composable-delivery/snowfakery-mcp/discussions)
- **Found a bug?** [Open an Issue](https://github.com/composable-delivery/snowfakery-mcp/issues) with a minimal recipe
- **Want to contribute?** See [CONTRIBUTING.md](CONTRIBUTING.md)
- **Security concern?** See [SECURITY.md](SECURITY.md)
## Development
```bash
# Install dev dependencies
uv sync --all-groups
# Run tests
uv run pytest
# Type check
uv run mypy snowfakery_mcp
# Lint & format
uv run ruff check snowfakery_mcp tests scripts evals
uv run ruff format snowfakery_mcp tests scripts evals
```
### Evals (Agentic Testing)
This repo includes `inspect-ai` tasks for testing the MCP server with AI models:
```bash
# Install eval dependencies
uv sync --group evals
# Run evaluation
uv run inspect eval evals/inspect_tasks.py@snowfakery_mcp_agentic --model openai/gpt-4o-mini
```
See [evals/](evals/) for more examples and troubleshooting.
## Notes
- The repo includes the upstream Snowfakery repo as a git submodule (`Snowfakery/`) for development
- When running from source, use `uv run ...` to ensure the pinned environment
- PyPI installs use bundled docs/examples (no submodule required)
## Releases
See [GitHub Releases](https://github.com/composable-delivery/snowfakery-mcp/releases) for sdist, wheel, and `.mcpb` bundles (recommended for Claude Desktop).