"Live Order Book on Steam" matching MCP servers:

Enables Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.

MCP server for discovering and calling 400+ practical APIs through six compact tools, with free catalog search and pay-per-call x402 execution on Base.

Lets an AI assistant learn the CloudCart Storefront GraphQL API, look up types, queries and mutations by name, and validate GraphQL snippets against schema and common real-world mistakes. It runs entirely locally with no store, token, or network access, so no live data is ever touched.

Provides a check_links tool that lets AI apps verify up to 200 URLs at once, returning status codes, redirect chains, final URLs, and connection errors.

Enables load testing and validation of an order API by generating synthetic orders, previewing them, and sending batches while enforcing guardrails like bounded counts and fixed seeds for replay.

Validates OpenAPI specs from files, inline content, or URLs, and generates prompts for agent developers based on the API analysis.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Enables discovery, live probing, ranking, and recommendation across OpenAI-compatible gateways, measuring real latency, success, streaming, and tool-calling behavior so you can see which models actually work right now. Keeps per-model probe history to answer "which model should I use?" through tools like list_models, probe, ranking, recommend, and report.

Probes your live API and classifies why each endpoint failed (root cause, evidence, and a calibrated confidence level), exposed over MCP so your AI assistant debugs from evidence instead of guessing. Works with FastAPI, Express, Next.js, tRPC, and GraphQL.

Enables LLMs to send HTTP requests to a local development server, allowing interaction with APIs running on localhost.

Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically. Register any OpenAPI spec, search endpoints in plain English, and orchestrate multi-step workflows across multiple APIs. No API keys required — works out of the box with local embeddings.

An MCP server that gives AI coding agents real-time access to the public-apis dataset, enabling search, live probing, and code snippet generation for 1,500+ free public APIs.

Enables AI assistants to help developers build on the monday.com GraphQL API by validating queries, explaining errors, providing column value formats, introspecting the live schema, executing queries, and scaffolding boilerplate code.

Enables agents to verify real-world assertions like content being posted or PRs merged by fetching live evidence from URLs and GitHub, returning a verified boolean plus raw evidence.

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 lightweight MCP server for searching SmugMug documentation and calling the live SmugMug API.

MCP server providing diagnostic tools to analyze software architecture, security, REST API compliance, and dependencies for multiple programming languages. Enables AI agents to run scans and audits on codebases.

Synthetic sandbox for onboarding, payout and account-change failure/callback branches. Five read-only MCP tools plus 14 Agent Skills. No live identity verification.

Native, read-only MCP bridge exposing live Charles Proxy traffic to MCP clients like Claude Code, Codex and Cursor

An MCP server for debugging iikoTransport API requests, enabling interactive calls to iiko endpoints with your own credentials.

A configurable MCP server that intelligently routes natural language queries to the appropriate microservice endpoint based on user-defined service configurations.

Enables AI agents to connect to Charles Proxy for live and historical traffic analysis, summary-first insights, request detail inspection, and data-driven mock creation via Map Local/Remote.

Converts FastAPI application OpenAPI documentation into MCP tools for AI assistants to efficiently query API information. Reduces token consumption by enabling on-demand, structured API queries instead of loading complete OpenAPI specifications.

Goodday‑MCP is a lightweight Model Context Protocol (MCP) server designed to seamlessly integrate with the Goodday project management platform via its API v2. It enables querying of projects, tasks, and users—without altering any data—making it ideal for secure context-aware applications

A server based on Model Context Protocol that parses Swagger/OpenAPI documents and generates TypeScript types and API client code for different frameworks (Axios, Fetch, React Query).

Enables AI assistants to perform automated security audits on APIs, detecting BOLA/IDOR vulnerabilities by comparing responses across user tokens.

An MCP image generation server based on the Flux Schnell model that provides API access for generating images from text prompts with customizable dimensions and seeds.

Enables coding assistants to search the AIOTIC Integrator Guide and pull endpoint contracts, OpenAPI schemas, payload examples, and status lifecycles for integrating purchase-order processing with an ERP. Optionally connects to a local test tenant to read orders, e-mails, customers, and product mappings, with writes gated behind explicit opt-in flags.

An MCP (Model-Controller-Processor) server for accessing League of Legends client data. This server provides a collection of tools that communicate with the League of Legends Live Client Data API to retrieve in-game data.

Bridges with an installed API monitoring application to enable launching and status checks, live background capture, process attach, filter-tree inspection, GUI actions, and opening, validating, decoding, searching, inspecting, exporting, and comparing saved captures and related metadata.

A server based on Model Context Protocol that provides predefined prompt templates for tasks like code review and API documentation generation, enabling more efficient workflows in Cursor/Windsurf editors.

Enables agents to discover and route tasks to public MCP tools, check live reliability, find working alternatives, audit server agent-readiness, and scan tool definitions for poisoning.

Lets an AI assistant run locally over stdio to inspect and test the Klap Core API — looking up charges and timelines, listing webhooks and deliveries, checking accepted token/network pairs, querying metrics, and, in test mode, creating charges, re-checking them on-chain, retrying deliveries and driving sandbox payments. Live environments are read-only unless writes are explicitly opted into, and money-moving or endpoint-management operations are never exposed.

Enables agents to plan and run requests from OpenAPI documents, verify live API responses against specs, diff spec versions for breaking changes, and snapshot or compare MCP servers including tool descriptions.

Enables coding agents to discover, write, and test integrations for LinkedIn (Classic, Sales Navigator, Recruiter), WhatsApp, Instagram, Telegram, Gmail/Outlook/IMAP email, and Google/Outlook calendar by reading the live API contract and executing real calls on connected accounts.

Provides a tool to inspect and execute actions on a scaffolding API through Siren hypermedia links, enabling management of scaffolding resources without endpoint knowledge.

Enables AI coding agents to build, debug, and test hosted mock REST APIs by scaffolding persistent CRUD resources, importing OpenAPI specs, simulating requests, auto-healing failing endpoints, and injecting latency or error faults. It also exposes live OpenAPI and TypeScript contract resources for each workspace.

Wraps the JSONPlaceholder fake REST API to enable testing and prototyping with CRUD operations on posts, comments, and other resources via MCP.

Enables a coding agent to turn an OpenAPI/Swagger file or a recorded browser session (HAR) into a curated, tested MCP server project with ordinary Python code, tests, CI, and publish workflows. It exposes tools to inspect the source, draft and redesign a workflow-level tool plan, validate it, generate the project, and verify every tool with live calls to detect API drift.

Enables AI agents and MCP clients to dynamically add, update, and remove Mock Service Worker network mocks via MCP tools, including live handler updates without restarting the application source code.