"Handling Sketch File Context and SVG Processing Overview" matching MCP servers:

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

A simple MCP server that can enable MCP clients to query Bluesky instances.

Enables AI agents to safely inspect a PortalV4 project's real structure, database schema, and Git status, while enforcing backend architecture rules, automating API documentation, and generating test templates without modifying repositories.

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.

Replay-verified minimal JSON reproductions and deterministic TypeScript/OpenAPI drift checks. Local-first CLI and MCP server.

Enables browser automation and API testing for AI agents using Playwright and Chrome DevTools Protocol, with numbered element references, Set-of-Mark screenshots, flow recording/replay, element memory, captcha handoff, and HTTP API test suites.

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.

A server that implements the Model Context Protocol for Schwab API, allowing access to account information, positions, stock quotes, and order/transaction history designed for integration with Large Language Models.

A Model Context Protocol server that requires user authentication via Auth0 before enabling secure API access on behalf of the authenticated user.

Enables AI assistants to query, filter, and analyze local HTTP capture records and REST API test data from the Reqable tool. It provides read-only access to inspect request/response details, headers, and statistics through natural language.

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.

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.

A proxy server that bridges AI agents and external APIs by dynamically translating OpenAPI specifications into standardized MCP tools, enabling seamless interaction without custom integration code.

A Model Context Protocol server that provides a standardized interface for interacting with the Tinder API, handling authentication, request processing, rate limiting, caching, and error handling.

Enables MCP-compatible clients to discover API endpoints from OpenAPI/Swagger specs, send HTTP requests, validate responses, and analyze status codes for automated API testing.

A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.

Official MCP (Model Context Protocol) server for Iron.xyz API, designed to work with Claude Desktop, Cursor IDE and other MCP compatible clients.

Enables AI assistants to interact with Fastly's CDN API through the Model Context Protocol, allowing secure management of CDN services, caching, security settings, and performance monitoring without exposing API keys.

Enables AI agents to lint API artifacts (OpenAPI, AsyncAPI, Arazzo) and manage rulesets conversationally via the Model Context Protocol.