"Identifying Vulnerabilities in Phishing Techniques and Analyzing Algorithms and Data" matching MCP servers:

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

A FastMCP-based server designed for the banking and fintech domains, providing tools for database queries, Git operations, and deployment management. It features a modular architecture with reusable prompt templates and integrated security practices for sensitive data handling.

Enables searching GitHub users and repositories, fetching details, and performing stock market technical analysis via AlphaVantage.

Pay-per-call MCP server offering crypto market signals, web page extraction, and GitHub repo auditing, with automatic settlement in USDC via the x402 protocol.

MCP server for Bitbucket Data Center that enables PR creation, review comment management, and rebasing workflows through natural language commands.

Provides MCP integration for Atlassian Data Center products including Jira, Confluence, and Bitbucket.

MCP servers for self-hosted Atlassian Data Center (Jira, Confluence, Bitbucket) enabling AI assistants to search, manage, and interact with issues, pages, and pull requests.

Enables AI applications to access and contextualize organizational knowledge sources including GitHub repositories and internal documentation through standardized MCP protocol integration. Features OAuth 2.1 authentication, vector-based semantic search, and optimized context chunking for enterprise development workflows.

A single-user MCP server that exposes your GitHub activity to Claude via three read-only tools: recent commits, open pull requests, and repository summaries. Deployed as a Vercel function using Streamable HTTP.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

myopic is a code-review MCP server that reviews GitLab/GitHub merge requests against the whole codebase, not just the diff, analyzing blast radius and conventions.

Quilt gives every AI agent line-level authorship in a shared Git checkout, so multiple agents work in one repo, and each commits only its own lines, with symbol-level claims that block collisions before any bytes change.

Repository-native protocol and MCP server for coordinating work items, documentation, changelogs, and project memory between humans and AI agents, using Markdown files in a Git repository as the canonical data source.

Enables detection and resolution of Git merge conflicts in repositories through MCP, providing tools to identify conflicting files and assist with conflict resolution workflows.

Automates the generation of professional worklogs by analyzing git commits with AI enhancement and seamlessly posting them to the Povio dashboard. It enables users to list projects, extract ticket numbers, and manage worklog entries through natural language commands.

Enables developers to find personalized open-source contributions by analyzing GitHub profiles and matching them with relevant 'good first issues' and beginner-friendly repositories. Provides comprehensive contribution tooling including repository health scoring, setup difficulty assessment, impact estimation, and automated PR planning.

Generates daily GitHub work summaries by analyzing commits across all repositories a user owns or contributes to. It provides tools to fetch today's commit activity and deduplicate repository-specific updates for easy reporting.

Analyzes GitHub Pull Request diffs for security vulnerabilities and data leaks, using a deterministic filter to skip trivial changes and an AI-powered analysis for logic changes.

Connects AI assistants to GitLab to interact with merge requests, reviews, discussions, pipelines, and test results through natural language queries. Supports viewing MR details, responding to comments, checking test summaries, and analyzing job logs.

Makes git commits on behalf of AI by appending "(aider)" to the committer's name, allowing tracking of AI contributions in your codebase.