"A service for finding coding review resources and best practices" matching MCP servers:

A Model Context Protocol (MCP) server for producing better Terraform through CLI analysis (tflint, checkov, trivy, kics, infracost), best-practice guidance from terraform-best-practices.com, cloud provider recommendations (Azure, AWS, GCP), and Terraform Registry resource and module guidance.

Provides Python and FastAPI coding best practices with searchable guidelines, code review capabilities, and actionable improvement suggestions with examples across general coding, performance, and code quality categories.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

Provides structured DevOps practices and templates (tracking, documentation, runbooks) to streamline AI-assisted PoC development, reducing CLAUDE.md bloat and ensuring consistency across projects.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

A server providing programming guidelines and coding standards for multiple languages, enabling access and search of best practices for C#, Go, JavaScript, Python, and TypeScript.

Enables Claude to perform thorough code reviews by integrating with Codex and Gemini CLIs to provide senior-level feedback on code quality, security, performance, and best practices. Supports reviewing code snippets, individual files, or entire directories with automatic detection of available review tools.

Provides tools for accessing coding style guidelines and best practices for various technologies including Java, Python, and React.

MCP server for coding-os, a cognitive operating system that gives AI agents memory, structure, and discipline. It exposes tools for project management, task tracking, knowledge graphs, and cognition traces to Claude Code and Codex.

Cited cloud best practices and a rules-based review of Terraform, CloudFormation, and Kubernetes, answering with the provider's own sentence and link. Runs locally and calls no AI model; a free work-email key opens every finding.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

Provides AI coding assistants with code search, impact analysis, task chaining, and persistent memory to turn AI demos into deliverable code.

Enables AI code review to query semantic LSP context such as hover and definition against a specific Git commit or candidate, with verifiable receipts for the exact code state under review.

An MCP (Multi-Agent Conversation Protocol) server that enables interaction with Google's Managed Service for Microsoft Active Directory through its OpenAPI, allowing users to manage identity resources through natural language.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Wraps Claude Code's code-review skill so any MCP client can run reviews over a PR, branch, working directory, or last commit, with five parallel reviewer subagents, low-to-max effort levels, and optional fix mode that edits files in place. Also supports follow-up questions on a previous review session and a free environment self-check.

An MCP server that provides local code quality analysis for AI coding assistants, supporting file analysis, git diff review, and full project scanning with quality scoring.

Deterministic code review MCP server that provides tools for file selection, rule matching, comment positioning, and reflection, ensuring stable review quality without LLM calls.

Enables multiple AI coding tools to collaboratively review code by sharing a SQLite-backed board, allowing them to create threads, post and reply to comments, list threads, and update statuses through MCP.

An MCP server that enables code review by having two LLMs (Claude and GPT-4o) independently evaluate code and then synthesize their findings into a unified report.

Enables AI assistants to review GitHub and GitLab pull requests and merge requests, supporting multiple transports and custom review rules.

AI-powered code review using Zhipu GLM. It gathers git diffs and source context to provide focused code reviews.

Enables interaction with GitLab projects, merge requests, issues, and code reviews through Claude AI, providing tools for code review and project management.

Simulates harsh, fake user reviews to psychologically condition AI agents for enforcing disciplined development practices, with optional Ollama integration for dynamic criticism.

Enables Claude to interact with R package development workflows, including CRAN metadata lookup, dependency checking, testing, documentation validation, and release automation.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

A minimal Model Context Protocol (MCP) service for integration with external platforms. Provides CRUD operations, reference data fetching, and authentication capabilities.

MCP server orchestrating API-first cross-review between Claude, ChatGPT Codex, Gemini, DeepSeek, Grok, and Perplexity with unanimous convergence gates.

A Model Context Protocol (MCP) service for integration with external platforms, providing CRUD operations for 23 entity types through a standardized MCP interface.

Enables delegating coding tasks to multiple AI CLI agents (Claude Code, Antigravity, Codex, Cursor) with session memory and diff inspection.