"Developing a FHIR-Based Digital Health Application with EHR, PHR, and Phenotyping Frameworks" matching MCP servers:

MCP server that helps AI agents inspect Minecraft project evidence (crash logs, mod files, datapacks) before writing development code.

Review and rewrite LangChain, LlamaIndex, Ollama, and XRPL code against current APIs, plus runnable examples, import lookup, and XRPL tx skeletons that never submit. Live docs included. $0.001 USDC on Base or 1000 drops XRP.

Privacy-first, read-only repo intelligence for AI coding agents: scans local codebases and recommends MCP servers, repos, and research without sending data to the cloud.

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.

Monitors and analyzes dependency health in Node.js projects, providing tools to check outdated packages, vulnerabilities, licenses, and suggest safe upgrades.

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

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.

Scores local git repositories for README substance, license, package description, TypeScript config, tests, and GitHub Actions, providing a numbered hygiene report.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Provides audit_plugin_health and prepare_semantic_review tools for deterministic inspection of Codex plugins and Agent Skills, generating evidence-backed reports without executing or transmitting target code.

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.

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Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

Enables checking whether software packages are deprecated, archived, stale, active, or unknown with supporting evidence, auditing dependency manifests, and looking up runtime support and end-of-life dates.

A no-train, on-prem code knowledge graph served over the Model Context Protocol, enabling AI agents to query code structure (symbols, calls, cross-language edges) with a tamper-evident audit log.

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.

A self-hostable, MCP-native RAG pipeline that ingests, indexes, and serves data, enabling AI agents to scan codebases for prioritized findings and integrate with CI workflows.