"Retrieve Website Titles Based on Given URLs" matching MCP servers:

An MCP server that performs code reviews by comparing local source code against design documents stored in Confluence. It integrates with Atlassian MCP servers to analyze documentation and provide suggestions for quality improvement based on design specifications.

A Model Context Protocol server that provides Angular project analysis and refactoring capabilities, enabling LLMs to analyze component usage patterns, dependency structures, and perform safe refactoring with breaking change detection.

Enables AI coding agents to navigate and understand entire codebases through symbol-aware semantic retrieval and relational call graph traversal, supporting structural impact analysis and code modification workflows over MCP.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

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.

An intelligent debugging assistant that automates the debugging process by analyzing bugs, injecting HTTP-based debug logs into code across multiple environments (browser, Node.js, mobile, etc.), and iteratively fixing issues based on real-time feedback.

Allows AI assistants to access and analyze your Cursor conversation history, enabling personalized coding assistance based on your actual development patterns.

A code review tool server based on Model Context Protocol (MCP) providing multi-dimensional code review and scoring.

Enables AI coding agents to submit work for external review before declaring a task done, receiving evidence-backed fix lists and verdicts based on git-measured changes and calibrated quality scoring.

Enables semantic code search across codebases with automatic incremental indexing. Searches return relevant code snippets with file paths and line numbers based on natural language queries.

MCP server to automate Pull Request creation with AI. Analyzes Git branches, generates descriptions, titles, suggests reviewers, and performs code reviews.

Slimdex is a local MCP server that helps coding agents retrieve code narrowly—outlines, line ranges, symbol bodies, references, and intent-based searches—instead of reading whole files into context, featuring a persistent index and tools for exploration, editing, and session memory.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

Analyzes codebases to suggest relevant learning projects and generate interactive slides with direct links to the Marble platform. It enables developers to create tailored learning experiences based on their specific technologies, patterns, and code context.

Provides code review and guideline loading based on Andrej Karpathy's coding principles, helping LLMs avoid common pitfalls like over-engineering and unnecessary changes.

Integrates Jira and Sourcegraph, enabling LLMs to retrieve and comment on Jira issues and perform code searches using Sourcegraph.

Enables users to retrieve, validate, and analyze XSD files from URLs or local paths, integrating with any LLM model.

Enforces AST-based architectural guardrails on AI-generated code, blocking writes that violate maintainability, security, or complexity rules and prompting immediate refactoring.

Enables coding agents to retrieve only the JavaScript/TypeScript code needed for a given task within a token budget, using TypeScript compiler analysis and a decision model to judge relevance.

TMF helps AI coding agents detect stale source context and retrieve source-linked code understanding on demand. It preserves traceable context across code paths so agents can consider upstream and downstream effects when making changes.