Reranker
БесплатноНе проверенA generic Model Context Protocol (MCP) server for high-accuracy document reranking using sentence-transformers (Cross-Encoder). Ideal for enhancing RAG and AI a
Описание
A generic Model Context Protocol (MCP) server for high-accuracy document reranking using sentence-transformers (Cross-Encoder). Ideal for enhancing RAG and AI agent decision-making. sentence-transformers (Cross-Encoder) を使用して文書の関連度を再計算・ソートする汎用 MCP (Model Context Protocol) サーバー。
README
A generic Model Context Protocol (MCP) server that provides document reranking capabilities using sentence-transformers.
This server is designed to be a standalone tool that can be used by any MCP-compatible client (such as Roo Code, Claude Desktop, or custom agents) to improve the precision of RAG (Retrieval-Augmented Generation) or to help agents make better decisions by scoring relevance between a query and multiple candidates.
💡 Proven in Production: This server was extracted as a general-purpose, reusable module from the cingulater project, where it is actively used and running in production.
Features
- Cross-Encoder Reranking: Utilizes the
CrossEncodermodel fromsentence-transformersfor high-accuracy relevance scoring. - Project Agnostic: Completely independent of any specific application logic.
- Customizable Models: Supports various HuggingFace models. You can configure the default model via environment variables (defaults to
BAAI/bge-reranker-v2-m3). - JSON Output: Returns sorted results in a structured JSON format.
Tools
rerank_documents
Computes relevance scores for a list of documents against a given query and returns them sorted by score.
Arguments:
query(string): The search query or the core intent to compare against.documents(array of strings): A list of document descriptions or texts to be ranked.model_name(string, optional): The HuggingFace model identifier. Defaults to theRERANKER_MODEL_NAMEenvironment variable or"BAAI/bge-reranker-v2-m3".
Response Example: A JSON-formatted string:
[
{ "document": "The most relevant document text.", "score": 0.985 },
{ "document": "A partially relevant text.", "score": 0.452 },
{ "document": "Completely irrelevant text.", "score": 0.012 }
]
Installation & Usage
Running with uvx
Add the following to your MCP configuration (e.g., brownie_core_mcp_config.json).
You can customize the model used by setting the RERANKER_MODEL_NAME environment variable.
{
"mcpServers": {
"mcp-reranker": {
"command": "uvx",
"args": [
"--from",
"git+[https://github.com/globalpocket/mcp-reranker.git](https://github.com/globalpocket/mcp-reranker.git)",
"mcp-reranker"
],
"env": {
"RERANKER_MODEL_NAME": "BAAI/bge-reranker-v2-m3"
}
}
}
}
Development
Prerequisites
- Python 3.10+
- uv
Setup
git clone [https://github.com/globalpocket/mcp-reranker.git](https://github.com/globalpocket/mcp-reranker.git)
cd mcp-reranker
uv sync --extra dev
Running Tests
uv run pytest
Установка Reranker
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/globalpocket/mcp-rerankerFAQ
Reranker MCP бесплатный?
Да, Reranker MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Reranker?
Нет, Reranker работает без API-ключей и переменных окружения.
Reranker — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Reranker в Claude Desktop, Claude Code или Cursor?
Открой Reranker на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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