"Finding popular airdrop tasks on cryptorank.io and completing them" matching MCP servers:

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PCI DSS v4.0.1 compliance scanner for Go payment services, delivered as an MCP server. Every finding maps to a specific PCI DSS requirement ID. Taint-aware cardholder data flow analysis with PCI SSC FAQ semantics, designed to complement broad SAST tools like Semgrep and CodeQL - not replace them.

Vet ClawHub skills before installing them; detects prompt-injection, exfiltration, and other security issues, outputting a risk score with per-finding evidence.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Exposes Semgrep as deterministic, rule-matching analysis tools over MCP so a code-review agent can scan only the lines changed in a diff, scan whole files on demand, and check analyzer availability, version, ruleset, and limits. Results are returned as compact per-finding lines with source snippets suitable as comment anchors, along with counts of suppressed out-of-diff matches.

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.

MCP server that guides LLM security reviews step-by-step, tracking progress and ensuring all assigned source code is read before completing each plan step.

Enables semantic and keyword search over a local codebase by chunking source files along function and class boundaries, embedding them offline, and fusing vector and BM25 results. Runs entirely on your machine in a single SQLite file, so AI coding agents can find relevant code with no API keys, telemetry, or cloud calls.

Enables AI coding assistants to perform local semantic code search using AST parsing and embeddings, finding code by meaning with exact file and line locations, plus AST-based usage lookup.

Indexes a workspace and exposes code-navigation tools to Codex, enabling symbol lookup, reference finding, dependency analysis, and security audit for local codebases.

Score your specs before an LLM builds from them. Scores on 4 axes (completeness, clarity, constraints, specificity), calculates a balance score, and returns a verdict with radar chart visualization.

MCP server that exposes code review tasks from the Fix My Comments VS Code extension to AI agents, enabling them to list, retrieve, reply to, and update task statuses.

Tracks latest versions and breaking changes for popular SDKs, enabling agents to check version updates and potential breaking changes efficiently.

Exposes boyter/scc code counting and complexity analysis to LLM agents via read-only tools like counting lines, finding top files, and cost estimation.

This MCP server assists Minecraft Java plugin developers by providing dependency documentation lookups, version checking, and automated scanning for Gradle and Maven projects. It supports popular APIs such as Paper, Spigot, and LuckPerms to streamline plugin development and workspace analysis.

Provides code refactoring capabilities for TypeScript/JavaScript and Python through Language Server Protocol integration. Enables renaming symbols, extracting functions, finding references, and moving code between files via natural language commands.

A Model Context Protocol server that helps AI code editors locate TypeScript symbol definitions in codebases, particularly useful for finding original definitions of imported symbols and classes.

Provides AI assistants with accurate Flyte V2 knowledge, patterns, and plugin information to help developers write correct Flyte code. It enables tasks like learning the V2 API, finding examples, selecting plugins, and migrating V1 code to V2.

Provides LLMs with safe, read-only access to local codebases for searching, reading files, and finding function definitions. All source code remains local, ensuring privacy while enabling AI assistants to explore project structures and functionality.

Automatically reads Sentry issues, investigates them by analyzing your Ruby codebase, explains why issues happened, and provides fix suggestions.