What Python version is required?
Python 3.10 or higher.
@MCP-Mirror
Basic information
Mirror of
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"OpenTorah-ai_mcp-sefaria-server": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"mcp-sefaria-server",
"--client",
"claude"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
A Model Context Protocol server that provides access to Jewish texts from the Sefaria library. It enables Large Language Models to retrieve and reference Jewish texts through a standardized interface using two main tools: get_text (fetch a specific text by reference) and get_commentaries (retrieve commentaries for a given text). Built with the MCP SDK and the Sefaria API.
Install via Smithery (npx -y @smithery/cli install mcp-sefaria-server --client claude) or clone the repository and run uv --directory path/to/directory run sefaria_jewish_library. Configure as an MCP server in clients like Claude Desktop or Cline by adding the binary command and directory to the client’s MCP configuration file.
Python 3.10 or higher.
Run `uv --directory path/to/directory run sefaria_jewish_library` from the command line, or configure it as an MCP server in a client (e.g., Claude Desktop) using the command and directory arguments.
Two tools: `get_text` (retrieve a text by reference) and `get_commentaries` (retrieve commentaries for a given reference). Both accept references in Hebrew or English.
No. The README does not mention any authentication or API keys; it uses the public Sefaria API.
Add a configuration entry under `mcpServers` with command `uv`, args including the directory and `run sefaria_jewish_library`, and the environment variable `PYTHONIOENCODING: "utf-8"` for Windows.

Local-first credential broker for MCP. AI coding agents (Claude Code, Cursor, Codex…) call APIs, SSH and databases through scoped presets; secrets stay in your OS keychain and never enter the agent's context.

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

Three.js MCP server and Claude Code plugin: screenshot, play, test and profile the three.js, React Three Fiber and WebGL pages your coding agent builds. paprika3d runs them in headless Chrome on a paused, seeded clock.
AptiBuild AI — Career Intelligence MCP Server Structured career decision scaffolding for AI agents. Provides personality-conditioned business idea generation, official BLS OEWS wage data, FRED labor market signals, and
Modelglass turns "which model should I use?" into a lookup instead of a guess. Seven tools give your agent live pricing across image, language, video, and audio models. Sourced and versioned, not scraped once and forgott
Comments