"Files" matching MCP servers:

MCP server that validates dashboardbase setup files and widget endpoint responses against the dashboardbase JSON contract, reporting errors and warnings before deployment.

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

An MCP server for parsing and analyzing HAR files, enabling AI assistants to inspect network traffic with automatic redaction of sensitive authentication headers.

Enables AI agents to create, run, and save API requests and collections as local Gud API files, which are git-committable and viewable in VS Code-compatible editors.

MCP server for API test case generation from Swagger/OpenAPI specs. Parses Swagger 2.0 and OpenAPI 3.x, generates test cases across 8 categories (positive, negative, boundary, auth, security, idempotency, pagination, business logic), and exports to Postman, TestRail, Allure, k6, pytest, Gherkin, and CSV. Supports internal corporate APIs with auth headers. Auto-saves export files to your working di

Generates comprehensive API test plans (positive, negative, and boundary/edge cases) from endpoint metadata using LLMs, and exports them as Excel files.

Discovers, inspects, and executes requests against OpenAPI or Swagger APIs directly from documentation URLs or specification files. It enables users to trace parameter usage across an API and perform authenticated HTTP requests through a structured toolset.

A Model Context Protocol server that creates tools from API configurations defined in YAML files, allowing easy integration of external APIs into an MCP ecosystem without coding.

Automatically converts Swagger 2.0 API specifications into MCP tools, enabling AI assistants to directly call REST APIs. Supports both local Swagger files and remote URLs with comprehensive parameter validation and error handling.

A Model Context Protocol (MCP) server that enables AI assistants to download files from URLs to the local filesystem.

Generates API documentation in Confluence from Swagger/OpenAPI specs or NestJS controller files, including automatic Postman collection generation.

Exposes SOAP-based web services as MCP servers by parsing WSDL files. Enables AI assistants to interact with legacy SOAP/WS-\* web services through the Model Context Protocol.

Dynamically creates an MCP server from ServiceStack API metadata configuration files, exposing typed REST APIs as MCP tools with support for filtering by tags or specific operations.

An MCP server that automatically converts OpenAPI specifications into MCP tools by scanning a folder for spec files, requiring no configuration files or separate servers.

A keyboard-first API client that stores requests and environments as plain files, and exposes its workspace over MCP so agents can browse, send, and create requests with vault access.

VCR for MCP servers: a zero-dependency stdio proxy that records and replays MCP JSON-RPC tool calls to local cassette files, enabling deterministic, offline testing of AI agent workflows without side-effects or rate limits.

A headless MCP server for Bruno workspaces, enabling CRUD operations on collections, folders, requests, environments, and dotenv files, plus request execution with scripting, tests, and assertions over HTTP, GraphQL, gRPC, and WebSocket.

Enables uploading and managing Postman collections, environments, and data files for API testing. Integrates with AI hosts via Model Context Protocol for test execution and result management.

An MCP server for calling gRPC methods from AI agents, enabling them to inspect gRPC APIs and invoke unary RPCs using server reflection or local .proto files.

A Bun-based MCP server that allows AI models to query Swagger/OpenAPI documentation from local files or remote URLs. It enables users to search for APIs, retrieve detailed endpoint definitions, and fetch schemas to facilitate code generation and API integration.