MCP Server

Connect AI Agents to Currents

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

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"
      }
    }
  }
}

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"
      }
    }
  }
}

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"

Permissions & Security

The MCP server authenticates with the configured CURRENTS_API_KEY, and every operation is limited by that API key's permissions. The server does not grant any access beyond what the key already allows.

• When the server is configured with a Read Only API key, all write operations (for example deleting a run, creating a webhook, or changing an action) are rejected by the Currents API with an HTTP 403 Forbidden - regardless of which tools the MCP server exposes to the agent.

• A Read & Write key allows the agent to perform write operations. A Read Only key is recommended when the agent only needs to read test results and analytics.

A dedicated key with the appropriate permission should be created to restrict what an AI agent can do through the MCP server. See API Keys for how to create and scope API keys.

Beware of destructive, irrecoverable operations. When used with a Read & Write key, the MCP server can perform permanent deletions with no confirmation step and no way to restore the data. Currently the irrecoverable tools are:

• currents-delete-run - permanently deletes a run and all associated data (test results, test records, instances, and analytics). This cannot be undone.

• currents-delete-webhook - permanently removes a webhook configuration.

• currents-delete-action - permanently removes an action.

Other write operations - such as currents-cancel-run, currents-reset-run, webhook and action creation/updates, and Jira issue creation/linking - are impactful but reversible. Grant a Read & Write key to an agent only when these capabilities are required.