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qverisai/mcp

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The MCP that lets you integrate a vast collection of tools into your AI agent with a single step.

Обзор

This repository is deprecated. The active @qverisai/mcp source now lives in QVerisAI/qveris-agent-toolkit/packages/mcp. Please file issues and pull requests in QVerisAI/qveris-agent-toolkit. Official QVeris MCP Server — Dynamically search and execute tools via natural language. This SDK provides a Model Context Protocol (MCP) server that enables LLMs to discover and execute third-party tools through the QVeris API. With three simple tools, your AI assistant can: - for tools using natural language queries - detailed information about specific tools by their IDs - any discovered tool with the appropriate parameters Add the QVeris server to your MCP client configuration: Once configured, You could add this to system prompt: "You can use qveris MCP Server to dynamically search and execute tools to help the user. First think about what kind of tools might be useful to accomplish the user's task.

README

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@qverisai/mcp

[!IMPORTANT] This repository is deprecated. The active @qverisai/mcp source now lives in QVerisAI/qveris-agent-toolkit/packages/mcp. Please file issues and pull requests in QVerisAI/qveris-agent-toolkit.

Official QVeris MCP Server — Dynamically search and execute tools via natural language.

Overview

This SDK provides a Model Context Protocol (MCP) server that enables LLMs to discover and execute third-party tools through the QVeris API. With three simple tools, your AI assistant can:

  • Search for tools using natural language queries
  • Get detailed information about specific tools by their IDs
  • Execute any discovered tool with the appropriate parameters

Quick Start

1. Get Your API Key

Visit QVeris to get your API key.

2. Configure Your MCP Client

Add the QVeris server to your MCP client configuration:

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "qveris": {
      "command": "npx",
      "args": ["@qverisai/mcp"],
      "env": {
        "QVERIS_API_KEY": "your-api-key-here"
      }
    }
  }
}

Cursor (Settings → MCP Servers):

{
  "mcpServers": {
    "qveris": {
      "command": "npx",
      "args": ["@qverisai/mcp"],
      "env": {
        "QVERIS_API_KEY": "your-api-key-here"
      }
    }
  }
}

3. Start Using

Once configured, You could add this to system prompt:

“You can use qveris MCP Server to dynamically search and execute tools to help the user. First think about what kind of tools might be useful to accomplish the user’s task. Then use the search_tools tool with query describing the capability of the tool, not what params you want to pass to the tool later. Then call a suitable searched tool using the execute_tool tool, passing parameters to the searched tool through params_to_tool. You could reference the examples given if any for each tool. You may call make multiple tool calls in a single response.”

Then your AI assistant can search for and execute tools:

“Find me a weather tool and get the current weather in Tokyo”

The assistant will:

  1. Call search_tools with query “weather”
  2. Review the results and select an appropriate tool
  3. Call execute_tool with the tool_id and parameters

Available Tools

search_tools

Search for available tools based on natural language queries.

Parameter Type Required Description
Открыть полный README на GitHub

Установка

npx @qverisai/mcp
Новичок в MCP? Начните с руководства на mcpskill.org →

Конфигурация

{ "mcpServers": { "qveris": { "command": "npx", "args": ["@qverisai/mcp"], "env": { "QVERIS_API_KEY": "your-api-key-here" } } } }