"Network Requests" matching MCP servers:

Captures browser network traffic, analyzes API patterns, and exposes analysis tools through an MCP server for AI-assisted workflows.

Enables LLMs to make HTTP requests with OAuth2, session cookies, retry logic, and cURL command generation, while providing security features like SSRF protection and TLS enforcement.

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

Run the requests in a Postman collection folder and get structured, assertion-level results back straight from your AI assistant.

Enables AI assistants to search, analyze, and debug application API traffic captured by Tusk Drift, including HTTP requests, database queries, distributed traces, latency metrics, and error rates.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

Captures incoming webhook/HTTP requests and lets AI assistants inspect, wait for, and replay them to debug webhook integrations.

Enables AI agents to create, run, and manage HTTP requests using the Invoker API client's .ivk format. It provides tools for scanning collections, executing requests, managing environments, and building documentation sites.

Enables MCP agents to create test webhook endpoints, read incoming requests, validate payloads against Hookline validators, and manage mock responses directly from the editor.

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

A generic MCP server that dynamically exposes any OpenAPI-documented REST API to LLMs by auto-discovering endpoints. It provides tools for exploring API capabilities and making authenticated requests directly through natural language interfaces.

Self-healing API proxy MCP that sends REST requests, diagnoses failures using Claude, patches requests, and retries. Successful fixes are remembered for instant reuse.

Enables interaction with Webhook.site to create, manage, and monitor endpoints for capturing HTTP requests, emails, and DNS lookups. It provides 16 tools for testing webhooks and inspecting incoming data through the Model Context Protocol.

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.

An MCP server that enables LLMs to make arbitrary HTTP requests (GET, POST, PUT, DELETE, etc.) with custom headers, bodies, and cookies, supporting JSON and error handling.

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

An MCP server for parsing and analyzing HAR files, enabling AI assistants to inspect network traffic with automatic redaction of sensitive authentication headers.

Universal HTTP client tool for LLM agents. Enables Claude and other MCP-compatible agents to perform GET, POST, PUT, DELETE, and other HTTP requests to any URL, including localhost and internal network addresses.

Enables AI coding agents to create webhook bins, inspect and replay HTTP requests, and stand up mock API endpoints directly from the editor.

Enables AI agents to send HTTP requests to any endpoint with full control over methods, headers, query parameters, and request bodies.