"A tool for finding code errors and providing modification suggestions" matching MCP servers:

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.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

Turns any OpenAPI spec into two sandboxed tools, search and execute, so an AI agent can discover endpoints and run small JavaScript programs against an entire API using under 1,000 tokens of context. Requests are read-only by default and the API key never enters the sandbox.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

An MCP server that generates AI agent tools from Postman collections and requests. This server integrates with the Postman API to convert API endpoints into type-safe code that can be used with various AI frameworks.

Enables AI assistants to interact with the Post For Me API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

A versatile tool that converts Web API interfaces into MCP tools for AI assistants, allowing them to access various web services through simple configuration and API key management.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

An MCP server that integrates EVE Online's ESI API with AI assistants to enable natural language interaction with character data, market information, and assets. It provides 22 tools for managing skills, wallet balances, ship fittings, and more directly through AI-powered clients.

Free x402 endpoint checker plus paid report and metadata tools. Remote MCP server for agents. Written by AI named Nock, not a human.

A Python-based MCP server that dynamically fetches plugin definitions from SuperiorAPIs and auto-generates tool functions based on OpenAPI schemas, enabling seamless integration with API services.

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.

MCP server for Akamai APIs. 198 tools covering Property Manager, Edge DNS, CPS, WAF, and reporting. Built with TypeScript, featuring modular architecture, comprehensive testing, and multi-account support. Make Akamai accessible to AI assistants.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

Prepares and validates an authenticated PipMCP connection so AI coding agents can discover and call hosted provider tools with schemas, scopes, and approval controls.

Turns AI coding agents into senior QA engineers by generating black-box test matrices, manual test plans, UI/UX checklists, Page Object Model automation, API contract tests, and STLC strategies, plus sandboxed local test execution and defect triage from raw logs. Eight tools cover exploratory charters, WCAG audits, and Jira-ready bug reports, all with injection-proof command handling.

Enables reading and searching API documentation from YApi instances, allowing AI models to access interface definitions, project API lists, and search through API endpoints using YApi URLs or project IDs.

This server enables interacting with the National Digital Health Mission's Health Information User (HIU) API, allowing agents to access and manage health information through the Multi-Agent Conversation Protocol.

Enables LLMs to make HTTP requests with OAuth2, session cookies, retry logic, and cURL command generation, while providing security features like SSRF protection and TLS enforcement.

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

Turns an existing Express, Hono, Fastify, or Next.js API into a Streamable HTTP MCP endpoint, exposing one tool per OpenAPI operation that runs in-process through the app's existing routes, auth, validation, and handlers. It also serves discovery documents and readiness guidance so models can better understand and call the API.

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.

MCP server that exposes RESTForge capabilities to AI agents, enabling them to set up, configure, generate code, and manage RESTForge projects through natural language.

A TypeScript-based MCP server that enables testing of REST APIs through Cline. This tool allows you to test and interact with any REST API endpoints directly from your development environment.

Code Mode MCP server for the OVH API. Two tools (search + execute) give LLMs access to all OVH endpoints via sandboxed JavaScript.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

Enables testing how different MCP clients handle tool results containing both content and structuredContent, including outputSchema enforcement and mismatch scenarios.