"Information about headers" matching MCP servers:

Enables LLMs to make HTTP requests using structured cURL commands with support for multiple authentication methods, custom headers, and comprehensive request/response control.

A minimal MCP server that enables HTTP requests with any method, headers, and body types, supporting large responses through chunked transfers with disk-backed caching.

A server that connects Claude with Spotify, allowing users to control playback, search content, get information about tracks/albums/artists/playlists, and manage the Spotify queue.

Enables interaction with the Twitch API, allowing users to retrieve comprehensive information about channels, streams, games, and more, with additional support for searching and accessing chat elements like emotes and badges.

Enables automatic HTTP requests (GET, POST, PUT, DELETE, etc.) with JSON validation and proxy support. Supports custom headers, request bodies, and environment variable configuration for seamless API integration.

An MCP server that dynamically converts any OpenAPI or REST API into MCP tools, allowing for real-time server switching and schema reloading. It supports variable substitution for headers and bodies, enabling seamless authentication and interaction with multiple API environments.

An MCP server that enables users to search Bilibili videos, access trending rankings, and retrieve detailed information about videos, content creators, and anime schedules. It allows AI applications to interact directly with Bilibili content via simple API interfaces.

Use Claude to control or ask questions about your Altium project.

Enables sending HTTP requests to webhooks with dynamic parameters, supporting all HTTP methods (GET, POST, PUT, PATCH, DELETE), custom headers, and configurable timeouts with detailed error handling and validation.

MCP server that allows AI assistants to query and retrieve information about office supplies inventory from a CSV file.

Provides vehicle data scraping from keplaca.com through the Model-Context Protocol, allowing users to retrieve detailed information about Brazilian vehicles using license plate numbers.

An MCP server that enables text extraction and replacement in Microsoft Word documents by directly automating the Word application on Windows. It supports processing content across headers, footers, tables, and shapes using the pywin32 library.

Enables LLMs to interact with the Pipefy GraphQL API to manage pipes, cards, database tables, and records through natural language. It provides tools for searching, creating, and retrieving detailed information about Pipefy workflows and database entities.

Enables full curl functionality within the Model Context Protocol, allowing users to execute network requests with support for custom headers and host networking. It facilitates interaction with local and external APIs, including those using self-signed certificates, directly through Docker.

Enables interaction with Google Chrome tabs through the MCP protocol, allowing clients to retrieve information and control tabs on macOS using AppleScript.

An MCP server providing AI assistants with comprehensive access to n8n node documentation, properties, and operations, enabling deep knowledge about n8n's 2,063 workflow automation nodes.

An MCP server for automating Turo peer-to-peer car rental interactions using stealth browser automation. It enables users to search for vehicles, view detailed listing and host information, and create or manage car bookings.

A TypeScript-based MCP server that enables AI assistants to execute HTTP requests with full control over methods, headers, and body content. It facilitates seamless interaction with web APIs and endpoints through a versatile tool that handles automatic JSON formatting and response truncation.

Enables AI assistants to control Spotify playback, search for music, manage playlists, and access library information through the Spotify API. Requires Spotify Premium for playback control features.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida