"Samsung Pay" matching MCP servers:

Enables AI agents to scan GitHub repositories and Robinhood Chain contracts for vulnerabilities, leaked secrets, dependency issues, and contract risks, returning scores, verdicts, and actionable fix plans as JSON with pay-per-call x402 access.

Provides coding agents with 19 pay-per-call developer utilities, npm supply-chain security checks, and Base blockchain lookups, paid via USDC on Base using x402. No API key needed—payment acts as authentication.

Provides npm/PyPI package intelligence including health scores, vulnerabilities, dependency graphs, and download counts via an MCP server, with optional pay-per-call access over x402 for advanced health and batch endpoints.

Enables AI assistants to search and read the official Open Play developer documentation and inspect TypeScript and Unity SDK symbols, signatures, and summaries.

Provides deep structural analysis of Python source code via AST, including function signatures, call graphs, cyclomatic complexity, code smells, dead code detection, and protocol conformance.

Enables AI-driven semantic code search via natural language queries, integrating with MCP clients like Claude Desktop to retrieve relevant code context from any codebase.

A Python MCP server for SonarQube, enabling AI agents to query projects, issues, quality gates, coverage, and security hotspots.

Provides a high quality cybersecurity tool platform with pay as you go pricing (no subscription).

Enables AI coding agents to query a local code graph over stdio, so they can see what a Git change may affect, find related tests, routes and nodes, and cite evidence paths — read-only and fully on-machine.

Enables AI assistants to perform comprehensive code quality checks including pylint, pytest, and mypy analysis on Python projects, with smart prompts for explaining issues and suggesting fixes.

Enables scanning repositories for TODO and FIXME markers while avoiding false positives in strings and URLs, then reports each marker’s age, author, and staleness using git blame and history. It also counts suppression signals, long functions, and commented-out code inside real comments.

Enables developers and agents to determine what licenses a project's dependencies use and whether shipping is permitted, combining SPDX parsing, installed metadata, lockfile readers, a compatibility table, and a policy engine whose verdicts always carry reasons.

Enables automated Python code quality checks including linting, complexity analysis, typo detection, structure validation, duplicate detection, and test coverage, with integration into Cursor IDE and CLI.

Enables an agent to mine a repository's git history and answer questions a new teammate would ask: which files are riskiest based on churn, recency and author breadth, who actually knows each file based on surviving lines, which files secretly change together, which directories depend on one person, and what recent commits mean for release notes. All analysis runs through a read-only server sandboxed to a single directory.

Enables an AI to risk-review Terraform and OpenTofu plan files over MCP stdio by summarizing plans, ranking dangerous changes, diffing resources with secrets masked, and comparing two plans without running Terraform.

Enables AI agents to inspect git working trees and history for exposed credentials without letting raw secrets reach the model, with false-positive filtering, baseline support, and remediation guidance.

Enables an AI to statically audit GitHub Actions workflow files, parsing YAML with accurate line numbers and reporting findings about on: key quirks, expression injection risks, unpinned actions, effective token permissions, and cron scheduling.

Enables an AI to statically lint Dockerfiles and compose files without Docker by parsing their true structure, reporting line-numbered findings with concrete fixes, and analyzing cache order, .dockerignore matching, and safe fix previews as diffs.

A Model Context Protocol server that gives Claude access to Google's Gemini 2.5 Pro for extended thinking, code analysis, and problem-solving with a massive context window.