"Debugging WebRTC SDK Implementation Issues in Visual Studio 2019" matching MCP servers:

An MCP server providing read-only access to Linear issues for language models, allowing them to fetch issue details and comments using a Linear API token.

Enables AI assistants to interact with the Roark REST API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Enables AI agents to create, edit, read, and run Bruno API collections (both .bru and .yml formats) with byte-parity to Bruno's own reader, without requiring the Bruno CLI.

An MCP server that demonstrates converting a safe OpenAPI subset into MCP tools and interactive apps, using the GitHub API as an example. It provides three GitHub tools with summary, table, and ranking views.

Enables AI agents to securely list, retrieve, and search Freshdesk support tickets through typed read-only MCP tools. It supports API-key authentication, rate-limit handling, safe logging, and an offline fictional demo mode.

Goodday‑MCP is a lightweight Model Context Protocol (MCP) server designed to seamlessly integrate with the Goodday project management platform via its API v2. It enables querying of projects, tasks, and users—without altering any data—making it ideal for secure context-aware applications

A Node In Layers package that simplifies creation of MCP (Model-Control-Protocol) servers with tools for defining models, adding CRUD operations, and interacting with clients.

Enables an MCP client to control Android emulators and iOS simulators, capture app traffic through a proxy, mark journey steps, and generate validated, correlated, parameterised JMeter scripts from the recordings.

MCP server that exposes WebSocket session management as tools, allowing AI agents to open persistent connections, send typed frames, drain buffered messages, and monitor per-frame Shannon entropy to detect schema divergence.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

MCP server for reading, writing, and organizing API documentation in Apidog.

Webhook management and testing tools for AI agents. Provides tools for sending, validating, generating, and debugging webhooks.

Runs, tests and edits the saved HTTP requests in a Kurlo API workspace (Git-backed YAML): list collections and environments, send requests with their auth and pm.* tests, write new requests and tests, and diagnose the last failure. Secret values are sent to the API but masked in every tool result, and protected environments are refused.

A small native HTTP client whose MCP server (plunger mcp) lets an AI agent send requests safely: undefined variables are refused, secrets are filled in by name and masked in results, and every request is recorded in a history you can see in the window. MIT licensed, for Windows, with a Linux build of the CLI and MCP server.

Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically. Register any OpenAPI spec, search endpoints in plain English, and orchestrate multi-step workflows across multiple APIs. No API keys required — works out of the box with local embeddings.

A standalone MCP server for API debugging, login authentication, API configuration management, and indexed API execution.

Enables LLMs to dereference and query OpenAPI/Swagger specifications, search endpoints and schemas, validate payloads, extract security schemes, and generate production-ready integration code in multiple languages.

MCP server for scanning smart contracts for security vulnerabilities. It detects issues like reentrancy, overflow, access control, and provides security scores with NEAR-specific recommendations.

Enables AI agents to create, run, and save API requests and collections as local Gud API files, which are git-committable and viewable in VS Code-compatible editors.

Enables AI coding assistants to discover, inspect, and run API requests in Bruno collections locally, keeping all data private.

An MCP server that enables AI assistants to control HTTP Toolkit for intercepting, inspecting, and debugging HTTP(S) traffic from browsers, mobile devices, and Docker containers. It provides tools for server management, interceptor activation, and sending HTTP requests through natural language commands.

Manages project standards, configurations, and API debugging for AI-assisted development, ensuring unified development practices across teams and machines.

Enables AI agents to read realistic, coherent data—repos, pull requests, issues, commits, users—through API-compatible, read-only replicas of 21 developer platforms including GitHub, Jira, Linear, Slack, Sentry and Salesforce, all preloaded with one simulated company so integrations can be built and tested with no accounts, credentials, rate-limit worry, or cleanup.

HTTP(S) and WebSocket debugging proxy, like Proxyman or Charles, that AI agents drive over MCP: summarize captured traffic, read requests with secrets masked, diff a working request against a failing one, mock responses, set breakpoints and throttle the network.

MCP server for ProxyKit — drive a local HTTP(S) debugging proxy from Claude, Cursor, and any MCP host.

A Model Context Protocol server that enables LLMs to interact with Plane.so, allowing them to manage projects and issues through Plane's API for streamlined project management workflows.

Enables direct integration with YApi API documentation platform in MCP-compatible editors like Cursor, allowing users to query API details, list interfaces, and search endpoints by simply pasting YApi URLs.

Enables AI to manage whistle mock rules, values, and inspect network sessions, facilitating API mocking and debugging through natural language.

Enables autonomous agents and CI pipelines to execute declarative multi-step REST API workflows in a single tool call, with in-memory variable chaining, assertions, and built-in SSRF protection.

Enables developers to search and access NicePay payment API documentation, including endpoint details, code samples, and SDK method information through natural language queries.