"Bitbucket pull request reviewer information" matching MCP servers:

Enables AI assistants to perform comprehensive code reviews of local uncommitted changes by combining git diffs with static analysis from linters like ESLint and TypeScript. Returns structured JSON feedback with findings, suggestions, and quality assessments powered by Google's Gemini CLI.

A code review MCP server built on FastMCP, supporting security audit, style check, complexity analysis, and bug pattern detection for Python code.

Code Reviewer AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Reviews MCP servers for quality, security, and best practices, providing scores and improvement plans.

MCP-first UI/UX review layer for AI-generated frontends. Enables reviewing web pages via URL, capturing screenshots, extracting layout metrics, and generating structured repair plans for agents.

An AI-powered server for code analysis, requirements validation, and automated fix proposals with human-in-the-loop confirmation. It supports multiple LLM providers and ensures safe file modifications through automatic backups and path validation.

A Bun-based MCP server providing a persistent HTTP request toolset for testing and inspecting JSON APIs. It supports session-aware operations, including cookie persistence, automatic bearer token reuse, and configurable base URLs.

Enables querying Codecov coverage data including file, commit, repository, and pull request coverage.

Enables recurring website maintenance checks — domain registration, SSL certificates, uptime, technical SEO and accessibility — across a portfolio of client sites, using publicly available information. Results are returned as structured data and can be sorted by urgency into a client-ready report.

Audits any site's UX the way a design-literate reviewer would — contrast, tap targets, type scale, colour discipline, scan patterns, copy — and returns the rule, the source line and the exact fix.

Enables coding agents to retrieve pull request review findings, reproduce and fix them locally, reply on review threads, report reproduction results, and request fresh reviews.

Enables Cursor AI to query SonarQube for pull request metrics, issues, file issues, and duplication reports directly, without manual data export.

An MCP server that gives AI coding agents the ability to analyze a Python repository's test health: coverage, flaky tests, and ML-based pull-request risk prediction.

A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.

Enables coding agents to drive and inspect running Shiny apps (R and Python) by setting inputs, clicking, reading outputs, and getting detailed error information.

Enables AI assistants to access RenderDoc capture data and assist with graphics debugging by retrieving draw calls, shader information, buffers, textures, and pipeline state.

Wraps Claude Code's code-review skill so any MCP client can run reviews over a PR, branch, working directory, or last commit, with five parallel reviewer subagents, low-to-max effort levels, and optional fix mode that edits files in place. Also supports follow-up questions on a previous review session and a free environment self-check.

An MCP server that makes backend API requests and packages request+response pairs as evidence to prove an endpoint works.

A local MCP server that connects Claude Desktop, Claude Code, and Claude Chat to your Azure DevOps organization, enabling querying work items, reviewing pull requests, triggering pipelines, searching code, managing test plans, and updating wikis using plain language.

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.