Skip to main content
Glama

mcp-reranker

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.

Features

  • Cross-Encoder Reranking: Utilizes the CrossEncoder model from sentence-transformers for 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 the RERANKER_MODEL_NAME environment 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

License

MIT License

Install Server
A
license - permissive license
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
2dRelease cycle
3Releases (12mo)

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/globalpocket/mcp-reranker'

If you have feedback or need assistance with the MCP directory API, please join our Discord server