"How to make a model aware of the current time before thinking" matching MCP servers:

Audits Make.com scenario blueprints before import, checking for hardcoded secrets, dangling references, plain-HTTP URLs, and other issues. Provides tools to inspect blueprint structure, trace module mappings, and generate a safety findings report.

Enables AI agents to turn raw calldata, transaction objects, JSON-RPC requests, EIP-712 typed data and personal_sign messages into short plain-English briefings covering what a request asks for, which risky allowances or permissions need attention, and what could not be verified. Runs entirely offline with no RPC, wallet, API key or safety verdict, using three read-only tools exposed to any MCP client.

Enables authenticated MCP clients to query Security Context tools against a git tag or commit ref while returning only vulnerabilities and fix fingerprints that predate that snapshot, so agents do not receive live bugs at the tag.

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 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.

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.

A local MCP daemon that turns an agentic coding client into a bug bounty operator, with 103 tools for offensive security testing including MITM proxy, traffic analysis, and OOB callbacks.

A production-ready MCP server that authenticates agents via OAuth 2.1 Bearer tokens, validates JWTs with JWKS, enforces tool-level scopes and roles, and logs the full delegation chain.

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

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

Enables AI coding agents to run one-shot commands and copy single files to and from remote servers through The Bastion, which authenticates, authorizes, and records each action. Access is controlled by the bastion rather than allowlists or deny lists.

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

Enables AI assistants to perform password security auditing using John the Ripper on a remote Kali system via SSH, supporting cracking, hash management, and session control.

the-real-unifi-mcp License: MIT Node MCP SDK [![CI](https://github.com/mguttmann/the-real-unifi-mcp/actions

Enterprise-grade code intelligence server for AI assistants that analyzes codebases for due diligence, tech debt, security vulnerabilities, and code quality.

Enables secure validation of agent credentials through constant-time digest comparison, JWT HMAC-SHA256 checks, Merkle inclusion proofs, Schnorr zero-knowledge verification, and nonce replay protection. It integrates natively with MCP clients to harden autonomous agent authentication workflows.

Local stdio MCP server for Bitwarden (Public API + Secrets Manager). 50+ admin tools for members, groups, collections, policies, licensing, projects, and secrets. For Claude Desktop / Claude Code.

Exposes LLM output validation (schema compliance and prompt-injection detection) as an MCP tool, enabling any MCP-compatible agent to apply real-time guardrails without importing the codebase.

A Python MCP server that authenticates users via Microsoft Entra ID, stores per-user data in Azure Cosmos DB, and provides admin tools based on Entra group membership.

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.

Living off the Land intelligence for AI agents. GTFOBins, LOLBAS, LOOBins, LOLDrivers, LOLRMM, WADComs, LOLC2 and more — unified into a single MCP server.

Enables authorized web/API security analysis as a stateful, multi-stage workflow with persistent session state, human-controlled validation, candidate versus confirmed finding tracking, and stop conditions.

Enables constant-time cryptographic attestation, zero-knowledge verification, JWT HMAC-SHA256 validation, Merkle proof inclusion, nonce replay protection, and secure digest comparison for agent security credentials via MCP.

A verifying MCP gateway that pins approved tool manifests and skill files to content addresses, blocking tampered descriptions before they reach model context.

ModelSafetyMCP is an MCP server for scanning machine learning model artifacts for unsafe serialization, malicious model patterns, risky packaging, URL-based artifact scanning, and directory-level triage.

IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real

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 executing arbitrary Joern/CPGQL queries against a loaded Code Property Graph, loading source code in multiple languages (PHP, Java, JavaScript, Python, C/C++) to build new CPGs, and inspecting loaded projects and the active workspace. It communicates with a running Joern server over its synchronous HTTP query endpoint, so no state polling is required.

A production-shaped starter for putting an MCP server in front of an existing app, with OAuth and enterprise SSO handled through Clerk, enabling AI assistants to act on your product on behalf of logged-in users.

Provides real-time content safety protection for large language models by detecting and preventing risks in both input and output content across multiple dimensions including compliance, ethics, and security.