@currents/mcp
MCP ServerFreeCurrents MCP server
Capabilities8 decomposed
playwright test execution orchestration via mcp
Medium confidenceExposes Playwright test execution as MCP tools, allowing Claude and other LLM clients to invoke browser automation workflows through a standardized tool-calling interface. Implements a schema-based function registry that maps Playwright operations (navigation, interaction, assertion) to callable MCP resources with structured input/output contracts, enabling LLMs to compose multi-step browser automation sequences without direct SDK knowledge.
Bridges Playwright's imperative test API with MCP's declarative tool-calling model, allowing LLMs to compose browser automation without learning Playwright syntax. Uses schema-based tool definitions to expose Playwright operations as first-class MCP resources with type-safe input validation.
Unlike generic Playwright wrappers or REST API adapters, this MCP server integrates directly with LLM tool-calling semantics, enabling Claude to reason about browser state and compose multi-step workflows natively.
currents test result aggregation and reporting via mcp tools
Medium confidenceExposes Currents cloud test reporting platform as MCP callable tools, enabling LLM clients to query test runs, retrieve failure summaries, and access CI/CD test metadata without direct API calls. Implements a schema-based wrapper around Currents' REST API that translates test result queries into structured MCP tool calls, with built-in filtering, pagination, and result formatting for LLM consumption.
Wraps Currents' REST API as MCP tools with LLM-optimized result formatting, including automatic summarization of large test result sets and flakiness detection. Implements client-side caching of test metadata to reduce API calls and improve latency.
Provides tighter integration with Currents' native reporting than generic REST API clients, with built-in understanding of test result semantics and automatic formatting for LLM consumption.
mcp server lifecycle management and tool registration
Medium confidenceImplements the Model Context Protocol server specification, handling client connection negotiation, tool schema registration, and request routing. Uses a declarative tool definition system where each Playwright or Currents operation is registered as an MCP tool with JSON Schema validation, enabling clients to discover available capabilities and invoke them with type-safe parameters.
Implements full MCP server specification with declarative tool registration, allowing zero-code exposure of Playwright and Currents capabilities to any MCP-compatible client. Uses JSON Schema for runtime validation of tool inputs, preventing invalid operations before they reach the underlying APIs.
Unlike REST API wrappers or custom integrations, MCP provides a standardized protocol for tool discovery and invocation, enabling seamless integration with Claude and other LLM clients without custom adapter code.
playwright screenshot capture and visual assertion support
Medium confidenceEnables Playwright test execution to capture screenshots and expose them as base64-encoded data or file references through MCP tools, allowing LLMs to perform visual assertions and analyze UI state. Integrates with Playwright's screenshot API to capture full-page, element-specific, or viewport-only images, with optional comparison against baseline images for regression detection.
Integrates Playwright's native screenshot capabilities with MCP's tool-calling model, enabling LLMs to capture and analyze UI state as part of automated workflows. Supports both direct image transmission (base64) and file-based references for large screenshots.
Provides tighter integration with Playwright's screenshot API than generic image capture tools, with built-in support for element-specific and full-page captures optimized for LLM analysis.
test failure context enrichment and error message extraction
Medium confidenceAutomatically extracts and structures error messages, stack traces, and browser console logs from failed Playwright tests, enriching them with contextual metadata (test name, duration, browser type) for LLM consumption. Implements a parsing layer that normalizes error output across different assertion libraries (Playwright's built-in assertions, Chai, Jest) and formats them as structured JSON for easier LLM interpretation.
Implements a multi-library error parser that normalizes failures from Playwright, Chai, Jest, and custom assertions into a unified JSON format optimized for LLM analysis. Automatically extracts and structures contextual metadata (browser type, duration, retry count) alongside error messages.
Provides deeper error context extraction than generic log parsing, with built-in understanding of test failure semantics and automatic categorization by root cause type.
browser context and session management for stateful test workflows
Medium confidenceManages Playwright browser contexts and sessions across multiple MCP tool invocations, enabling stateful test workflows where subsequent operations inherit browser state (cookies, local storage, authentication) from previous steps. Implements a context registry that persists browser instances and page objects between tool calls, allowing LLMs to compose multi-step workflows without re-initializing the browser for each step.
Implements an in-memory context registry that maintains Playwright browser instances across MCP tool invocations, enabling stateful workflows without re-initializing the browser. Uses context identifiers to allow LLMs to reference and reuse browser sessions across multiple tool calls.
Unlike stateless browser automation tools, this capability enables persistent browser sessions across LLM tool invocations, reducing overhead and enabling complex, multi-step user journey automation.
currents ci/cd metadata extraction and test run correlation
Medium confidenceQueries Currents API to retrieve CI/CD metadata associated with test runs (commit hash, branch, build ID, author), enabling LLMs to correlate test failures with code changes and build context. Implements a metadata enrichment layer that combines test result data with Git and CI/CD information, providing LLMs with full context for root-cause analysis and impact assessment.
Enriches Currents test results with Git and CI/CD metadata, enabling LLMs to correlate failures with code changes and build context. Implements automatic metadata correlation based on test run timestamps and CI/CD system references.
Provides deeper context than test-only APIs by automatically correlating test results with Git commits and CI/CD builds, enabling LLMs to perform impact analysis and root-cause investigation.
flaky test detection and historical trend analysis
Medium confidenceAnalyzes historical test execution data from Currents to identify flaky tests (tests that fail intermittently) and track failure trends over time. Implements statistical analysis of test pass/fail rates across multiple runs, with configurable thresholds for flakiness detection and trend visualization data for LLM interpretation.
Implements statistical flakiness detection on Currents historical data, calculating pass/fail rates and trend indicators for LLM-driven test quality analysis. Uses configurable thresholds to identify tests that fail intermittently and track improvement/degradation over time.
Provides automated flakiness detection beyond simple pass/fail tracking, with statistical rigor and trend analysis that enables LLMs to prioritize test stabilization efforts.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
Artifacts that share capabilities with @currents/mcp, ranked by overlap. Discovered automatically through the match graph.
@currents/mcp
Currents MCP server
mcp-evals
GitHub Action for evaluating MCP server tool calls using LLM-based scoring
playwright-mcp-server
MCP server for generating Playwright tests
@executeautomation/playwright-mcp-server
Model Context Protocol servers for Playwright
Currents
** - Enable AI Agents to fix Playwright test failures reported to [Currents](https://currents.dev).
mcp-playwright
Playwright Model Context Protocol Server - Tool to automate Browsers and APIs in Claude Desktop, Cline, Cursor IDE and More 🔌
Best For
- ✓QA engineers building AI-assisted test automation workflows
- ✓Teams integrating Playwright tests into LLM-powered agents
- ✓Developers prototyping browser automation agents with Claude
- ✓DevOps engineers building AI-assisted test failure analysis
- ✓QA teams integrating Currents reporting into LLM workflows
- ✓CI/CD pipeline owners automating test result interpretation
- ✓Developers integrating Currents MCP into Claude Desktop or custom LLM applications
- ✓Teams building internal AI-assisted testing platforms
Known Limitations
- ⚠Requires Playwright to be installed and configured in the same environment as the MCP server
- ⚠No built-in test result persistence — results are ephemeral unless explicitly captured by the client
- ⚠Limited to Playwright's supported browsers (Chromium, Firefox, WebKit); no support for legacy IE or mobile-specific browsers
- ⚠Execution is synchronous per tool call — parallel test execution requires client-side orchestration
- ⚠Requires valid Currents API credentials and active Currents account
- ⚠Read-only access to test results — cannot modify or re-run tests through MCP tools
Requirements
Input / Output
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Currents MCP server
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