"Information about backend development or backend systems" matching MCP servers:

Enables interaction with Qonto's Business API for banking operations. Supports all API key-accessible endpoints for managing business banking transactions and account information.

Enables developers to access kintone API specifications, field type documentation, and development best practices through natural language queries. Supports API request validation and provides comprehensive development guidance for kintone customizations.

Enables AI assistants to manage API endpoints, environments, and testing workflows through the GASSAPI backend. Provides semantic documentation tools for endpoint cataloging and automated flow creation for backend-to-frontend development workflows.

Enables AI assistants to interact with AccelByte Gaming Services APIs through semantic search, detailed API information retrieval, and authenticated API execution for game backend operations.

MCP Portico is an MCP server that turns OpenAPI descriptions or inspected backend source code into policy-controlled MCP connections, exposing multiple backend systems with tenant isolation and credential security.

A TypeScript-based MCP server that provides backend API handling and facilitates communication between microservices. Features an organized structure with controllers, routes, and models for easy extensibility and maintenance.

Exposes backend APIs through Azure API Management as an MCP server to enable AI assistants to interact with product catalogs and order systems. It provides standardized tools for searching products, retrieving details, and managing orders via the Model Context Protocol.

A universal bridge that turns legacy backend services and modern APIs into AI-accessible tools without requiring code rewrites. It dynamically generates tool definitions from WSDL, OpenAPI, or custom JSON specs to enable AI assistants to interact with systems like SAP, IBMi, and SOAP services.

Enables agents to query real-time OpenAPI documentation of backend services, providing tools to list services, endpoints, and schemas via MCP.

Enables AI agents to connect to any GraphQL endpoint, introspect schemas, and execute queries or mutations through auto-generated tools.

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.

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

An MCP server for interacting with Treasure Data API, allowing users to retrieve database information and check server status through natural language queries.

Enables LLMs to send HTTP requests to a local development server, allowing interaction with APIs running on localhost.

Enables AI assistants to fetch and understand API endpoint definitions from Apifox projects in real-time. Supports retrieving complete API specifications including request methods, parameters, headers, and response schemas to improve development efficiency and code generation quality.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

An MCP server that makes backend API requests and packages request+response pairs as evidence to prove an endpoint works.

Enables turning any docs URL (OpenAPI, llms.txt, or HTML) into lean, callable MCP tools with add/list/call operations, plus timeout and truncation guards.

Precisely filter and fetch API documentation from Apifox or any OpenAPI URL, reducing context bloat by fetching only needed endpoints.

Enables AI agents to create disposable webhook URLs, capture incoming HTTP requests, inspect headers and bodies, and replay them against local or remote endpoints, streamlining the webhook handler development loop.