"Using Claude to Check the Current Weather Without an API Key" matching MCP servers:

Human-in-the-loop approval: a person approves the exact AI action with a passkey, and any service can check the signed approval offline.

Turns any OpenAPI REST or GraphQL API into an MCP server, allowing AI assistants like Claude to interact with APIs without writing code.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

A proof-of-concept MCP server that scopes GitHub tools to the current repository without filesystem access, using MCP roots to carry the repo identity.

Converts any REST API endpoints into MCP tools, enabling AI clients like Cursor and Claude Desktop to call internal services directly.

Enables validation of commit messages, branch names, author info, push safety, and repository state using commit-check rules, accessible as MCP tools.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

Provides a stable, side-effect-free MCP tool contract that enables AI workflows to be prototyped, demoed, tested, or dry-run without connecting to databases, APIs, files, or other real data sources. It enables swapping in a real data server later without changing the AI-facing interface.

Enables Claude Desktop and other AI tools to interact directly with Figma, allowing for powerful AI-assisted design capabilities through natural language commands.

Enables coding agents to publish HTML pages and small sites over MCP, returning a stable link and keeping every version, with access limited to specific people, an organization, or anyone with the link.

Enables Tavily and Firecrawl MCP servers to operate with multiple API keys, automatically rotating to backup keys on quota exhaustion, rate limits, or invalid keys, while rewriting API endpoints to the local proxy.

Enables an agent to submit a task brief and receive a short, validated list of skills from its full catalogue that are worth reading before starting.

Scores any remote MCP server for readiness across the Claude Directory, ChatGPT Apps, Gemini Connected Apps, and MCP Registry, returning a 0–100 score, A–F grade, per-store status, failing checks, and one-line fixes. Also provides report links, badges, and explanations of each check.

MCP server that enables AI agents to read, analyze, and modify Figma designs, including comment management via Figma's REST API. Works with any Figma account and supports parallel execution.

Enables AI agents to check the live operational status of hundreds of cloud, SaaS and AI providers, returning current state, affected components and active incidents for a named stack so agents can tell a vendor outage apart from their own broken code. It answers from a continuously polled local database, so agents can query stacks, list degraded providers, and review incident history without calling vendor status pages.

Provides authoritative open source license answers: SPDX identification, copyleft classification, and compatibility checks of dependencies against your project's license.

Read-only Supabase RLS check: explains in Arabic which tables anyone can read or change. No keys.

MCP server for managing i18n translation files — gives your AI agent full control over your app's translations without dumping entire locale files into context.

Explains cron expressions in plain English, checks them for errors and gotchas, lists next run times in any time zone, and converts between Unix cron, GitHub Actions, Kubernetes, AWS EventBridge, Quartz and Spring dialects.

Enables MCP clients to inspect Minecraft Java Edition datapack files using the Spyglass language server, returning diagnostics for syntax, JSON schema, and references via MCP stdio.

Runs SQL statements in memory against real PostgreSQL 18 and SQLite 3.49 engines after loading your schema and sample rows, returning each statement's own verdict: errors with line, column, and hints, constraint violations, or the resulting rows. It also compares both dialects to expose portability differences, all with no database server, network, or API key.

Runs a regular expression on real engines — JavaScript (V8), Python (CPython re), PCRE2 and RE2 — reporting each engine's own compile errors with positions, every match with its groups and named groups, replacement results, and where the engines disagree. It also detects catastrophic backtracking (ReDoS), naming the at-risk part of the pattern, generating an attack string, and timing how long each engine actually takes on it.

Enables an AI assistant to inspect project dependency and runtime files, determine each component's support status and end dates, and rank upgrade urgency using bundled endoflife.date data.

Enables reviewing GitHub Actions workflows for outdated actions, deprecated Node runtimes, retired runners, deprecated commands, and security risks, with file, line, and fix for each finding.

Local-only GitHub Actions and CI maintenance scanner for AI-built apps. Exposes scan, explanation, and fix-planning tools to MCP clients; modifies nothing and makes no outbound requests by default.

Enables agents to validate JSON, JSONC, YAML, and TOML configuration files against official SchemaStore schemas, pinpointing errors and likely key misspellings, and to look up schema-backed setting details.

Enables agents and users to validate Kubernetes manifests (YAML/JSON, multi-document) against the API of a chosen Kubernetes version without needing a cluster. It reports removed or deprecated APIs with replacements, unknown or misspelt fields, misconfigurations the API server would reject, Pod Security Standard violations, and common risks, each with file, line, and fix.

Enables agents to validate Dockerfiles for build-breaking syntax errors, risky patterns like root users and secrets in ENV/ARG, and cache-order problems, returning every finding with its line and a fix. It also verifies referenced container images against public registries, reporting tag existence, digests to pin, supported platforms, last rebuild time, and end-of-life status with an upgrade tag.