mcp-grade Alternatives

mcpscore is an open-source CLI tool that analyzes MCP servers for compliance, quality, and protocol validation. It generates comprehensive reports to help developers and administrators ensure their Model Context Protocol servers meet required standards.

mcpvet is an open-source CLI tool that combines testing, linting, and contract validation for MCP servers. It integrates with pytest and ESLint, streamlining the development and quality assurance process for developers working with the Model Context Protocol.

MCP Scoreboard is a web-based analytics platform that provides independent quality scores for public MCP servers. Users can browse, compare, and track server reliability, access data via API or CLI, and receive score alerts. It is designed for MCP server operators and ecosystem participants.

mcp-mcts is an open-source CLI tool for local MCP security scanning, attack chain analysis, inventory management, and CI integration. It supports optional Semgrep and LLM analysis, making it suitable for security engineers and DevOps teams focused on codebase security.

mcp-strike is an open-source command-line tool designed for active, runtime adversarial testing of Model Context Protocol (MCP) servers. It helps security engineers and red teams identify vulnerabilities and weaknesses by simulating attacks and scanning for issues. The tool supports automated security assessments and is freely available under the MIT license.

MCP Score is an independent trust registry for MCP servers. It assigns MCPScore values on a 0–100 scale and is described as security-first, with the stated goal of showing when things get worse. The registry scores each server on security, freshness, adoption, quality, and trust. Its methodology is public and versioned, and the site shows how those factors combine into the overall score. The homepage also surfaces several views built around those scores, including top by score, most downloaded, new arrivals, security risks, and score drops. It includes a compare function, search, and filters for registry source and score thresholds. The directory covers 46,736 scored servers and says it is updated nightly. Listings shown on the page include the server name, registry source such as npm or PyPI, weekly download counts, and star counts where available. The browse area groups servers by categories such as Databases, Dev Tools, Web Scraping, Automation, AI & ML, Finance, Monitoring, Communication, Search, Storage, and Other. The site describes itself as independent and states that it takes no vendor money. It is delivered as a website at timeahead.in, with paths for servers, blog, and about.

mcp-audits is an open-source CLI tool that scans, enumerates, and risk-scores permissions on locally configured MCP servers. It is designed for security engineers and AI infrastructure operators to ensure safe and compliant access control in AI systems.

mcp-checkup is an open-source CLI utility that audits MCP server setups, measuring context tax and hygiene. It helps AI infrastructure engineers and developers ensure their Model Context Protocol servers are efficient and healthy by providing detailed health checks and token analysis.

mcp-top is an open-source CLI tool that profiles the context footprint and usage of local Model Context Protocol (MCP) servers. It helps AI infrastructure engineers monitor and optimize server resource usage.

mcp-explorer is a command-line interface tool that allows developers to explore and interact with MCP (Model Context Protocol) servers. It provides utilities for discovering available capabilities, testing endpoints, and understanding server configurations directly from the terminal. Licensed under Apache-2.0 and distributed via PyPI, it is designed for developers building or integrating with MCP-based AI agent systems.

mcp-migration is a command-line tool that scans MCP server source code or probes live servers to assess migration readiness for the 2026-07-28 specification. It detects hidden session state, deprecated primitives, and generates detailed compliance reports for developers maintaining MCP servers.

mcp-ctrl is an open-source command-line tool that enables developers to manage and orchestrate Model Context Protocol (MCP) servers for Claude Code and other large language models. It supports Docker and Podman environments, making it easier to deploy and control LLM infrastructure. Ideal for AI engineers and developers working with MCP and LLM workflows.

MCPfinder is a free, open-source discovery and installation layer designed for AI agents to locate and configure Model Context Protocol (MCP) servers. It serves as an MCP server itself, enabling AI assistants to programmatically search multiple MCP registries, inspect trust signals, and generate install-ready JSON configurations for downstream MCP servers. The tool is intended primarily for AI agents, with humans only needing to install it once; after installation, the AI assistant can use MCPfinder repeatedly to expand its capabilities on demand. Key features include multi-registry search, aggregating MCP servers from the Official MCP Registry, Glama, and Smithery into a unified search interface. MCPfinder allows AI agents to find candidate servers by keyword, technology, or use case, inspect trust signals and required environment variables, and generate client-specific configuration snippets suitable for platforms such as Claude Desktop, Cursor, Claude Code, Cline, or Windsurf. The tool provides structured outputs, including confidence scores, recommendation reasons, warning flags, and install complexity, helping AI assistants make informed decisions about which servers to recommend or install. MCPfinder is delivered as an MCP server that can be added to any MCP-compatible AI client. Installation is flexible, supporting direct execution via NPX (no install needed), global installation with NPM, or project-based integration. Once installed, it operates as an always-up-to-date agent-facing layer, bootstrapping from published snapshots and syncing from upstream registries. This ensures that AI agents have access to the latest available MCP servers and their metadata, with freshness signals provided by snapshot manifests. 0 and is free to use, with the source code available for inspection, contribution, or forking. MCPfinder is built by the community for the community, and as of its latest published snapshot, it aggregates tens of thousands of MCP servers across multiple registries. Its focus on agent-native discovery, trust signal inspection, and install-ready configuration distinguishes it as an AI-centric solution within the ecosystem of MCP tools.

MCP Servers is a marketplace and discovery platform that enables users to search for and explore a variety of MCP servers, clients, command-line tools, integrations, and reusable workflows. The platform is organized into categories such as Developer Tools, AI & Agents, Cloud & Infrastructure, Memory & Knowledge, and Media & Design, making it easier to find production-ready servers and related resources. The service highlights featured servers and clients, including those supporting payments, analytics, code editing, and database management. It lists both remote and local servers, as well as official and agent-ready CLI tools for tasks like JavaScript runtime management, database querying, audio/video processing, and cloud development. MCP Servers also showcases reusable prompts and workflows, referred to as "loops," which can automate tasks such as testing, accessibility auditing, code coverage, and continuous integration monitoring. In addition to servers and CLI tools, the platform features agent skills tailored for AI agents, covering areas like brainstorming, systematic debugging, writing plans, and skill invocation. These resources are designed to facilitate the connection of AI applications to various tools, data sources, and automated workflows. The platform also provides a feed of trending and newly published servers, offering insights into what the community is installing and using. MCP Servers is aimed at developers and those building AI-powered applications who need to integrate diverse tools and automate workflows. The platform is web-based and includes a registry of available servers, clients, and integrations.

code-review-agent-mcp is a Model Context Protocol (MCP) server that delivers direct, technically rigorous code reviews modeled after kernel maintainer feedback. It uses AI to analyze code with blunt honesty, focusing on correctness, performance, and maintainability without diplomatic language. The tool is distributed as a PyPI package under the MIT license.

mcp-cve-lint is a static analysis tool that lints MCP (Model Context Protocol) server configuration files. Each rule is directly mapped to a real-world MCP-related CVE or GHSA, helping developers catch security issues early. It is primarily used by AI engineers and backend developers implementing MCP servers.

mcp-tool-auditor is an open-source command-line tool designed for security researchers to scan and pentest MCP servers. It provides both defensive scanning and offensive pentesting capabilities, mapping to the OWASP MCP Top 10. The tool helps identify and mitigate security vulnerabilities in AI and LLM-related infrastructures.

Test your MCP server like you test an API — declarative YAML, CI-ready, zero boilerplate.

MCPForge is an online service for verifying Model Context Protocol servers. It addresses the need for security and production readiness checks before deploying AI agents that rely on these servers. The service supports two primary analysis methods. Users can connect directly to a live MCP server using Streamable HTTP, SSE, or STDIO transports for a protocol handshake. Alternatively they can submit an OpenAPI 3.x or Swagger 2.x specification, a URL, or a Postman Collection v2.1, with the system automatically detecting the format. Analysis covers security posture, protocol compatibility, compliance signals for GDPR, PCI, and SOC2, tool quality, and health with latency metrics. Output consists of an MCPForge Score from 0 to 100, security findings, recommendations, a shareable report URL, and an option for a README badge. It operates as a web-based tool that requires no account for basic use and delivers results in seconds. The site demonstrates compatibility with servers from various providers including GitHub, Stripe, Shopify, Notion, Slack, Supabase, and PostgreSQL, though these examples serve only for demonstration and carry no affiliation. A free tier is available with paid options referenced in the navigation.

MCP Pre-Flight is a submission audit tool for MCP servers being prepared for Claude and OpenAI directories. It is meant to catch the kinds of mismatches that reviewers reject before a submission goes in, and it presents that check as a three-layer process covering wire-level checks, per-tool invocation, and source-side AST analysis. Its wire-level tests cover OAuth 2.1 with PKCE, dynamic client registration, authorize, token exchange, refresh, and MCP protocol endpoints including initialize, tools/list, and tools/call, along with malformed-body and unknown-method resilience. At the tool level, every safe-to-invoke tool is actually called with synthesized arguments, and idempotent tools are probed by calling them twice and comparing the results. The source-side analysis is optional and accepts a GitHub repo URL; it runs an AST check to compare handlers against annotations, checks that the README mentions every declared tool, and analyzes response language for vocabulary that contradicts annotations. Findings are tagged by directory, with each issue marked for Claude or OpenAI. The service is aimed at developers submitting MCP servers to those directories. Its FAQ says the input should be the HTTPS endpoint of a deployed MCP server using Streamable HTTP transport, and that the server should respond to JSON-RPC tools/list. It also notes that if OAuth is present, the full auth flow is tested, and that an optional test bearer token unlocks authenticated MCP checks. Source probing uses the GitHub API, and the page says pre-flight only probes the live endpoint; if source is checked later through the M8ven Trust Index, the repository is cloned in an isolated sandbox and then deleted. MCP Pre-Flight is offered as a free web tool. The page also states that Claude and OpenAI directories require OAuth for listed MCPs, and it mentions an OpenAI domain challenge file at /.well-known/openai-apps-challenge for OpenAI submissions.

ml-trainer-mcp is an open-source MCP server that enables training and evaluation of machine learning models using MCP tools. It provides both CLI and API interfaces for ML engineers to automate and standardize their workflows.

mcp-risk-linter is an open-source CLI tool that analyzes MCP server tools for readiness and security risks, including authentication, filesystem, shell, and network vulnerabilities. It helps developers and DevOps teams ensure safer deployments.

mcptrends provides data-driven insights into the adoption of Model Context Protocol (MCP) servers. It offers momentum rankings, trend analysis, and leaderboards to help developers and organizations identify the most promising MCP implementations. CLI and SDK are planned for deeper integration.

Lookup MCP servers in the official MCP Registry by name or URL.

mysql-mcp-pro is an open-source MCP (Model Context Protocol) server that provides a secure, production-grade interface between AI agents/LLMs and MySQL databases. It offers connection pooling, transaction management, query analysis with EXPLAIN, data export in CSV/JSON, ER diagram generation, audit logging, and built-in prompt templates. Designed for developers integrating AI tools like Claude or Cursor with relational databases.