"Using SocialBu API to Upload Content to Social Media" matching MCP servers:

Turns any OpenAPI REST or GraphQL API into an MCP server, allowing AI assistants like Claude to interact with APIs without writing code.

Converts any REST API endpoints into MCP tools, enabling AI clients like Cursor and Claude Desktop to call internal services directly.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

Enables publishing content to multiple social media platforms (YouTube, Twitter, Facebook, Instagram, TikTok, Reddit, Blog) through automation agents, with task management and system validation.

Connects to multiple social media platforms (Twitter/X, Mastodon, LinkedIn), allowing users to create and publish content across platforms through natural language instructions.

A Model Context Protocol (MCP) server for managing social media posts, currently supporting X (formerly Twitter).

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

Enables social media account management including content calendars, posting cadence, captions, hashtags, engagement strategies, metrics interpretation, and client reporting.

Enables checking email addresses through the Email Social Media Checker API to verify and validate email information.

Connects AI assistants to a social workspace so they can read brand context and saved analytics, create reviewable drafts, schedule approved campaigns at future times, and access permissioned research. Scheduling, credit usage and paid refreshes stay explicit and separate from draft creation.

A bridge that enables any LLM to access and interact with documented REST APIs through the Model Context Protocol (MCP).

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Converts REST API code (like NestJS controllers or FastAPI endpoints) to Postman collections and environments, helping developers automatically sync their API endpoints with Postman.

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.

Enables converting text to speech audio in 20+ languages, returning base64-encoded MP3 output via Google TTS with x402 micropayment-based pay-per-call access.

Converts any OpenAPI/Swagger spec into an MCP server, exposing REST API endpoints as tools for Claude.

Enables converting Markdown text into clean HTML for headings, lists, code blocks, tables, links, and images, with optional full-document wrapping via x402 micropayments.

Enables AI agents to convert CSV text into JSON arrays with automatic delimiter detection and optional header-row handling, accessed through a pay-per-call x402 micropayment API.