"A tool to manage and process a list of Swagger API endpoints" matching MCP servers:

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

An MCP server that sends plain-text Gmail messages only to a predefined allowlist, using generated recipient IDs instead of email addresses to enforce security.

MCP server that acts as an adapter to a shopping list web application, using OAuth 2.1 with Keycloak for secure authorization.

Supply chain risk scoring for npm, PyPI, and GitHub repos

A hosted Model Context Protocol server that lets AI agents triage review queues, investigate authors, tune policies and wordlists, respond to incidents, configure projects and webhooks, and report on moderation activity through a Moderation API account.

Enables agents to prove and verify that a real, unique human performed an action, issuing machine-readable signed credentials with public verification.

Enables centralized proxy and orchestration of MCP servers, providing unified tool discovery, authentication, and secure request routing. It adds a human-in-the-loop approval gate for high-risk actions and audit logging.

Provides agent certification and trust verification tools for AI agents, enabling certification checks, trust score calculations, audit ticket issuance, and emergency kill switch activation through the A-SOC trust network.

Enables declaring a catalog of tools for LLMs, filtering them by role, validating arguments, guarding sensitive calls with server-side confirmations, and recording an audit log.

An MCP server that manages a TODO list with user authentication via Stytch, enabling AI agents to interact with a full-stack application.

A secure tool-execution plane for agentic AI that enforces JWT authentication, rate limiting, prompt-injection inspection, and audit logging, while ingesting downstream OpenAPI endpoints as MCP tools.

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

Enables agents to search across the pooled tools of many connected MCP servers and invoke them through a single endpoint, returning only the handful of tools relevant to each request. Filters by the caller's permissions before ranking, so agents never see or plan around tools their user is not allowed to use.

Enables AI agents to securely discover, invoke, and manage tools through a hardened MCP endpoint with protections like injection detection, circuit breakers, retry backoff, response caching, context-window limiting, and state snapshots.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.

Governed MCP server for bank-grade agent tool access with RBAC, PII redaction, rate limiting, and audit logging.

Enables MCP tool handlers to be declared with a decorator, collected into a registry from a config map, and served over a bearer-token-authenticated Streamable HTTP ASGI app. Tools can also be invoked in-process without running any HTTP server.