"Information about CoinGecko API or Node Integration" matching MCP servers:

A powerful and flexible Node.js Express server that provides a comprehensive interface to the CoinGecko cryptocurrency data API. This server supports both the free public API and the Pro API with automatic fallback.

An MCP server that generates MCP servers. Give it an API definition - OpenAPI 3.0/3.1 or a Postman collection or extend an existing server - and it scaffolds a complete, runnable, ownable TypeScript or Python MCP server for that collection of APIs.

Turns an OpenAPI spec into a ready-to-run test harness with local LLM agents: WireMock stubs, contract tests, robustness probes, and chaos scenarios you can switch on and off in a running WireMock.

Enables AI agents to execute HTTP/REST/GraphQL requests against any endpoint, including private VPN hosts and local services, while logging untruncated headers, request bodies, and raw responses into a local SQLite audit history. Agents can then search that history by keyword, date, method, or status, retrieve full details by ID, and export everything to JSON.

Enables validating API responses against expected schemas/JSON and listing OpenAPI endpoints to enforce API contracts between services.

Provides implementation guidance, code validation, and troubleshooting tools for Searchspring's e-commerce APIs including search, autocomplete, recommendations, and tracking. Helps developers properly integrate Searchspring functionality with platform-specific code examples and best practices.

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.

A Model Context Protocol server that connects Gemini CLI with CoinGecko's API, enabling users to access 46 cryptocurrency data tools including price tracking, market trends, and NFT information through terminal commands.

Enables interaction with Nullplatform's API endpoints for managing deployments, scopes, services, and other cloud resources through natural language using the official OpenAPI specification.

Exposes REST API endpoints defined in an OpenAPI Specification as MCP tools, allowing AI models to call them via the ModelContext Protocol.

Enables agents to invoke any REST or SOAP service by sending a normalized payload, with support for API key, Basic, Bearer, and OAuth2 auth. Connectors can be registered once and reused by name.

Connects external APIs like Open-Meteo and AgroMonitoring to your development environment through URI-like requests, allowing access to live data directly in MCP-compatible tools.

Enables agents to discover how a website serves its data, verify sources with evidence, export OpenAPI 3.1, and generate tested TypeScript or Python clients.

Enables instant creation of mock API servers from OpenAPI specs or natural language descriptions, with built-in fake data generation, CRUD endpoints, and configurable delays/errors for testing.

Enables natural-language chat-driven API testing, letting users upload API specs, run deterministic pytest checks against live targets, inspect results, create defects, and view failure trends.

Enables testing and interacting with any REST API endpoint directly from MCP clients like Claude and Cline, supporting GET, POST, PUT, DELETE and PATCH requests with detailed response information, custom headers, and Basic, Bearer or API key authentication.

Enables agents to analyze OpenAPI contracts for deterministic integration risks, plan auth, sync, action, and webhook candidates, and diff contract versions for likely breaking changes through read-only tools.

Enables LLMs to make arbitrary HTTP API requests with any method and full control over headers, query parameters, and body.

Enables read-only exploration of YApi projects, categories, and interface docs, and deterministic TypeScript/JavaScript API request function and type generation through a preview-then-apply workflow.

Starter scaffold for a workshop to build an MCP API testing server, intended to be extended through incremental steps.