"Local Health Risk and Safety Guidance for COVID-19, Flu, RSV, and Other Illnesses in the US" matching MCP servers:

An MCP server that audits DeepSeek Harness (DSH) plugins for security threats using static and dynamic analysis. It enables automatic safety reviews of community plugins before installation, detecting risks like credential theft and prompt injection.

Enables security scanning of code projects to identify common vulnerabilities like XSS, injections, SSRF, and path traversal issues. Provides local, offline scanning with severity-grouped results and actionable fix suggestions for improving code security.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Assesses code change risk with ultra-low token budget (50-100 tokens) and provides structured risk metadata for AI agents in IDEs.

Validates and tests llguidance grammars (Lark format), providing grammar validation, batch test execution, and syntax documentation.

Provides comprehensive code quality analysis with quantitative metrics, historical trends, and refactoring risk prediction for C#, Python, and TypeScript codebases.

An MCP server that performs comprehensive health checks on project dependencies for JavaScript and Python projects, detecting outdated packages and fetching changelogs.

An MCP server that provides AI agents with real-time package health data, vulnerability reports, and dependency graphs from PyPI and OSV.dev.

Enables scanning projects for dependency vulnerabilities, secrets, license conflicts, code quality, and git health, returning a 0-100 health score with actionable suggestions.

Provides read-only repository health scanning tools for drift detection, module reachability, prompt bloat, evidence calibration, and registration completeness, enabling agents to diagnose repositories via MCP.

Provides MCP tools to check a package's maintenance status, licence, and security advisories before you depend on it, with per-call payment in USDC on Base mainnet via x402.

Indexes commit history to create a queryable expert, providing insights into code evolution, developer intent, and hidden patterns beyond static code analysis.

Monitors and analyzes dependency health in Node.js projects, providing tools to check outdated packages, vulnerabilities, licenses, and suggest safe upgrades.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

A fully local RAG MCP server for semantic code search and code intelligence, using AST-level chunking and hybrid search to pinpoint functions, classes, and APIs. No cloud, no API keys, zero setup.

Provides 28 MCP tools across 16 analysis engines for comprehensive Python code quality assessment, including complexity scoring, security scanning, dead code detection, dependency auditing, and test quality analysis.

Delegates heavy, repetitive, and verifiable tasks like PDF extraction, code analysis, and log processing to a local LLM to reduce token consumption for frontier AI models, while keeping decision-making with the main AI.

A local MCP server that indexes codebases using Tree-sitter AST parsing and LanceDB, enabling AI models to search across repositories with sub-second latency.

A Model Context Protocol (MCP) server that enables AI applications to access and analyze local code repositories without manual uploads, providing file listing, content reading, code searching, and project structure analysis capabilities.

Enables AI to precisely use local Vue components by extracting their Props, Events, and Slots via AST analysis.