Valyu MCP Server

Name: Valyu MCP Server
Author: valyu-network

@valyu-network

代码仓库

关于 Valyu MCP Server

Typescript implementation of MCP server for Valyu Network API (https://docs.valyu.network/api-reference)

#valyu #mcp #server #api #knowledge-retrieval

基本信息

分类

其他

许可证

MIT

运行时

node

传输方式

stdio

发布者

valyu-network

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "valyu-mcp-js": {
      "command": "docker",
      "args": [
        "pull",
        "ghcr.io/tiovikram/valyu-mcp-server"
      ]
    }
  }
}

工具

Search proprietary and/or web sources for information

Submit user feedback for a transaction

概览

What is Valyu MCP Server?

Valyu MCP Server is a Model Context Protocol server that provides access to Valyu's knowledge retrieval and feedback APIs. It enables LLMs to search proprietary and web sources for information and submit feedback on transactions.

How to use Valyu MCP Server?

Install via Docker (docker pull ghcr.io/tiovikram/valyu-mcp-server), set the VALYU_API_KEY environment variable, and configure the server in your MCP client (e.g., Claude.app). Invoke the knowledge tool to search sources or the feedback tool to submit user feedback.

Key features of Valyu MCP Server

knowledge tool to search proprietary, web, or all sources
feedback tool to submit user feedback for transactions
Supports configurable search parameters (query, max price, data sources, etc.)
Sentiment ratings: very good, good, bad, very bad
Docker image ready for easy deployment

Use cases of Valyu MCP Server

Searching for information across proprietary and web data sources
Submitting user feedback and sentiment for a specific transaction
Integrating knowledge retrieval directly into an LLM workflow

FAQ from Valyu MCP Server

What tools are available?

Two tools: knowledge for searching information and feedback for submitting user feedback on transactions.

What arguments are required for the knowledge tool?

A query (string), search_type ("proprietary", "web", or "all"), and max_price (number, maximum CPM allowed). Optional arguments include data_sources, max_num_results, similarity_threshold, and query_rewrite.