"Server Security Help and Guidance" matching MCP servers:

Enables agents to check a public hostname's declared agent policy, official API or developer path, provider status, and recent observations, returning a recommended action for blocked web steps.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Standalone MCP server exposing only the security-classified tools from Shade Browser, enabling Brave CDP browser automation across 20 isolated profile slots. Built on FastMCP and Playwright Python.

Provides a security governance layer for AI agents to safely access upstream MCP servers, enforcing tool-level RBAC, parameter constraints, authentication via static tokens or OIDC, and tamper-evident audit logging.

Hey @roocode community! I'm thrilled to share a project born from my work with Roocode and the vision of an AI-powered development team: the Anubis MCP Server! This system is heavily inspired by Roocode and designed to orchestrate an AI development workflow based on agile methodology. It simulates

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables AI agents to securely reach enterprise tools and other agents through a governed gateway with pinned tool definitions, delegated authorization, content inspection, human approval, and signed audit trails.

Enables a Claude Code cloud session to run shell commands inside a chroot jail on your own computer and to call the MCP servers already installed there, with every request authenticated and relayed over a Cloudflare quick tunnel so no router port is opened and no SSH key or tunnel is ever handed to the cloud VM.

Exposes Amazon Nova Act web automation capabilities through the Model Context Protocol, enabling AI agents to perform browser tasks like navigation, data extraction, and form interaction.

Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.

Acts as an intermediary between LLMs and other MCP servers, centralizing management, sanitizing sensitive information, and providing a unified interface for discovering and interacting with proxied MCPs.

Enables Grok Bots to install, verify, build, seal, unseal, list, and update hash-pinned skill packs from static URLs, expanding skill capacity beyond template limits without executing pack content.

Paid hosted MCP for agent-to-agent compute routing and brain-builder workflows. OAuth 2.1 + PKCE auth, Stripe prepaid USD credits, 29 tools (10 free, 19 metered). 25% of net revenue funds verified conservation via a public auditable ledger. SEP-1960 manifest and SEP-1649 server card published.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

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

Human-in-the-loop approval gate for MCP agents, classifying tool calls by risk and requiring Slack-based human approval for medium/high risk actions.

An authless Cloudflare Workers server that provides tools to scrape, analyze, and answer questions about websites using Cloudflare's Browser Rendering and AI capabilities.

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.

Enables a local LLM to ask the user for guidance via a native desktop pop-up dialog, with configurable options and multiple-choice or free-text input.