Jewish Library MCP Server

@Sivan22

About Jewish Library MCP Server

makes the jewish library accessible to LLMs through the MCP protocol

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-otzaria-server": {
      "command": "uv",
      "args": [
        "--directory",
        "path/to/directory",
        "run",
        "jewish_library"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Jewish Library MCP Server?

Jewish Library MCP Server is an MCP (Model Context Protocol) server that provides powerful full‑text search capabilities for Jewish texts and literature. It enables Large Language Models to search and reference Jewish texts through a standardized interface.

How to use Jewish Library MCP Server?

Requires Python 3.10 or higher. Clone the repository, download and extract the search index from a Google Drive link, install dependencies with pip install ., then run the server using uv --directory path/to/directory run jewish_library or through any MCP client.

Key features of Jewish Library MCP Server

Full‑text search across Jewish texts and literature
Advanced query syntax: field‑specific search, boolean operators, required/excluded terms, phrase search, wildcards
Relevance‑based scoring
Rich search results with reference information, topics, and highlighted excerpts
Single MCP tool: full_text_search

Use cases of Jewish Library MCP Server

Search for specific passages by reference, topic, or textual content
Combine multiple query fields to refine searches (e.g., text + topics)
Integrate Jewish text lookup into LLM‑based applications for research or education
Perform complex searches using boolean logic and wildcards

FAQ from Jewish Library MCP Server

What query syntax does the full‑text search support?

It supports field‑specific search (text:, reference:, topics:), boolean operators (AND, OR), required/excluded terms (+term, -term), phrase search ('exact phrase'), and wildcards (?, *).

What are the runtime requirements?

Python 3.10 or higher, MCP SDK >= 1.1.1, Tantivy search engine, and a separately downloaded pre‑built search index.

How do I download the search index?

The search index is provided as a single file from a Google Drive link mentioned in the README. It must be extracted into the index/ directory inside the project.

Where does the server store its data?

The server uses a local index/ directory for its search indices. No external database or cloud storage is required beyond the initial index download.

Does the server support authentication or multiple transports?

No authentication mechanism or transport options beyond the standard MCP protocol are documented.

Frequently asked questions

What query syntax does the full‑text search support?

It supports field‑specific search (`text:`, `reference:`, `topics:`), boolean operators (`AND`, `OR`), required/excluded terms (`+term`, `-term`), phrase search (`'exact phrase'`), and wildcards (`?`, `*`).

What are the runtime requirements?

Python 3.10 or higher, MCP SDK >= 1.1.1, Tantivy search engine, and a separately downloaded pre‑built search index.

How do I download the search index?

The search index is provided as a single file from a Google Drive link mentioned in the README. It must be extracted into the `index/` directory inside the project.

Where does the server store its data?

The server uses a local `index/` directory for its search indices. No external database or cloud storage is required beyond the initial index download.

Does the server support authentication or multiple transports?

No authentication mechanism or transport options beyond the standard MCP protocol are documented.

Comments

Basic information

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