"ERPNext enterprise resource planning software" matching MCP servers:

Enables MCP-capable agents to search the curated gold-402 directory of x402 services, probe any endpoint for valid 402 payment terms, and optionally purchase a human editorial verdict for a resource.

Provides comprehensive documentation for 377 Fortnox API endpoints and 81 resource categories directly from the official OpenAPI specification. It enables users to search, browse, and explore technical endpoint details and data schemas within AI assistants without requiring authentication.

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.

Enables interaction with Google Ads through the Google Ads API using GCloud authentication. Supports GAQL query execution, performance data retrieval, account management, and resource discovery with pagination and multiple output formats.

DreamFactory MCP Server enables AI assistants like Claude to directly query your databases through DreamFactory's auto-generated REST APIs. This Node.js server implements the Model Context Protocol (MCP), allowing natural language database interactions while maintaining enterprise-grade security.

Generates standalone, human-readable MCP servers from RAML 1.0 or OpenAPI 3.x specs, exposing one tool per resource and method that makes real HTTP calls. It understands Mule/Anypoint auth patterns such as Client ID enforcement and OAuth2, wiring the expected credentials from environment variables at call time.

Provides comprehensive development tools for Magic-API including documentation lookup, API testing, resource management, debugging with breakpoints, backup operations, and code search capabilities. Enables developers to efficiently build, test, and maintain Magic-API projects through natural language interactions.

A proof-of-concept MCP server implementing OAuth 2.1 authorization with CIMD client registration and PKCE, demonstrating protected resource access and step-up authentication.

Enables MCP clients to exercise HTTP tools against an upstream service, secured via bearer-token authentication, along with a resource and prompts.

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.