"Chat with RAG (Retrieval-Augmented Generation)" matching MCP servers:

Enables post-hoc auditing of an agent's retrieval supply chain by recording digest-only provenance from source through chunk, transformation, context and decision, then reporting influence rankings with an honest unexplained residual, lineage traces, advisory source trust and retirement recommendations, and retrieval schema drift. It never performs retrieval, ranks documents at query time, or blocks decisions.

MCP server that integrates Apache Ranger authorization with RAG, enforcing Ranger policies to control access to knowledge bases before forwarding queries to RAG Studio.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

Enables permission-checked search of past chat history that links older messages with the latest activity, returning supporting context such as timestamps, speakers, and surrounding conversation. Authorization is re-verified against current room membership and approved groups on every search, message fetch, and period read.

A wrapper for mcp-remote that provides secure authentication for protected MCP servers using Adobe IMS or Okta OAuth flows. It features automated token management, validation, and background refreshing for seamless access to remote resources.

Enables role-based order management through MCP tools, allowing users to view and refund orders according to their permissions (USER, MANAGER, ADMIN) with audit logging and JWT authentication handled by a FastAPI client.

Provides 14 MCP tools for AI agent infrastructure, enabling knowledge base queries, skill search, handoffs, blueprint validation, trust scoring, identity verification, SLA validation, and compliance checks.

Demonstrates how to secure an MCP server with OAuth 2.1 using AWS Cognito, with support for dynamic client registration and client ID metadata documents.

Enables secure filesystem access with privacy controls using .mcpignore files to block MCP clients from reading or writing sensitive files and directories while allowing directory browsing and search.

A Cloudflare Workers-deployed MCP server that provides secure remote access to MCP tools through GitHub OAuth authentication. Includes example tools for basic math operations, user info retrieval, and image generation with configurable user access controls.

An example MCP server that allows remote clients to connect and authenticate using WorkOS AuthKit, providing organization-centric authentication with permission-based access control for tools.

A minimal example MCP server using Express and Clerk for authentication, exposing a streamable HTTP endpoint for MCP clients.

Exposes AI-augmented network reconnaissance and evasion capabilities as callable FastMCP tools, enabling natural language orchestration of host discovery, service fingerprinting, CVE mapping, and attack chain synthesis.

This MCP server implements a secure OAuth 2.1 authorization server with Google login, enabling authenticated tool execution and a user interface for MCP applications.

This MCP server provides authentication via wallet sign-in (SIWE) and authorization with scoped access to read and trade portfolios, enabling secure portfolio management through natural language.

Enables deploying a secure MCP gateway that proxies, sandboxes, and policy-governs third-party MCP servers, with credential vaulting and audited tool access across stdio, SSE, and Streamable HTTP.

Exposes standard MCP tools for secure calculation, knowledge-base retrieval, document statistics, and sensitive operations like email, export, and deletion with human-in-the-loop approval.

Enables natural language analysis of network packet captures, including protocol detection, flow analysis, and security threat identification, integrated with AI assistants.

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Enables AI agents to safely read and write files in a sandboxed workspace via natural language, with on-demand connection, CVE-hardened path confinement, injection resistance, and full audit logging.