Skip to content

Latest commit

 

History

History
89 lines (68 loc) · 2.35 KB

File metadata and controls

89 lines (68 loc) · 2.35 KB
description Connect AI Agents to Currents
icon message-bot

MCP Server

What is MCP

MCP stands for Model Context Protocol. It's an open pattern, introduced by Anthropic, that provides a consistent way for systems to expose tools and resources that can be used by AI models.

Currents MCP server is a context layer for AI tools that leverage information about Playwright test results, such as failed tests, errors, and more.

Get started

Install our NPM package

npm install @currents/mcp

Setup the MCP Server

{% tabs %} {% tab title="Cursor" %}

  1. Go to Cursor Settings > MCP > Enable
  2. Add the following to your mcp.json
{
  "mcpServers": {
    "currents": {
      "command": "npx",
      "args": [
        "-y",
        "@currents/mcp"
      ],
      "env": {
        "CURRENTS_API_KEY": "your-api-key"
      }
    }
  }
}

{% endtab %}

{% tab title="Claude " %} Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "currents": {
      "command": "npx",
      "args": [
        "-y",
        "@currents/mcp"
      ],
      "env": {
        "CURRENTS_API_KEY": "your-api-key"
      }
    }
  }
}

{% endtab %} {% endtabs %}

Example Prompt

@folder Tests are failing in CI. Get all the details from the run <runId> fix the failures

Get the runId from the run's "Advanced" tab in the dashboard. Soon, the MCP server will be able to fetch the latest runs for an organization, removing the need for users to provide a specific run id.

Use Cases & Capabilities

Currents MCP server exposes a variety of tools to retrieve projects, runs, test results, and performance metrics.

For a complete and up-to-date list of available tools and their usage, please refer to the Currents MCP GitHub Repository.

These tools can be used to provide context to the AI agent about all the details of a run, test executions, and specs, including historical data like error rate, debugging logs, duration, flakiness, and more.

Here are some examples of AI prompts:

  • "Please fix this test"
  • "Summarize my last test run"
  • "What were the top flaky tests in the last 30 days?
  • "What were the slowest specs in the last 7 days?"
  • "Please fix all my flaky tests"