"Agentic Wallet Guardian" matching MCP servers:

A self-hosted decision engine that sits between an AI agent and blockchain execution. Agents submit a proposed action, Guardian returns an explainable ALLOW / WARN / BLOCK before anything gets signed or broadcast.

Read-only MCP server that exposes the agentic-os governance, SDLC, and Quality Engineering methodology to any MCP host. It never writes to your repository and never executes code — it serves the methodology, plans an install, and verifies it, handing any commands back to the host to run.

Enables AI agents to query Austria's entire company register (Firmenbuch) in plain language, providing official master data, annual accounts, and key ratios from a multi-tenant MCP server.

A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.

OWASP Agentic - MCP server providing AI-powered tools and automation by MEOK AI Labs

An MCP server that lets multiple agent sessions (e.g., Claude Code, Claude Desktop) on the same machine communicate over shared channels like walkie-talkies, enabling them to exchange messages and coordinate tasks without any central broker.

Klarna-style product discovery for AI shopping agents. Makes product catalogs machine-readable so AI agents can search, compare, and purchase products programmatically.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

Read-only MCP server for accessing Wallet by BudgetBakers financial data, allowing users to query accounts, transactions, categories, budgets, and more via natural language.

Machine-readable detection lookups for SIEM enrichment and AI agents. Query 800+ LOLBAS and GTFOBins binaries plus process parent-child baselines — get risk levels, abuse categories, and MITRE ATT\&CK mappings without embedding data in prompts.

Provides comprehensive financial analysis and real-time market data including stock information, options chains, technical indicators, financial statements, earnings calendars, and market sentiment indicators through integration with yfinance and other financial APIs.

Agentic Hardware-in-the-Loop (Agentic HIL) lets coding agents develop firmware on real embedded boards: flash, reset, read UART and exchange CAN traffic, diagnose and fix. Local, policy-gated MCP tools support OpenOCD, pyOCD and STM32CubeProgrammer, with pytest for CI.

A deterministic, read-only MCP server that enforces license headers in tracked Python files without requiring network access or repository mutations. It provides a specialized tool to verify license compliance through standardized, network-free analysis.

A simple MCP server demonstrating tools, resources, and prompts for weather data, built during an Agentic AI Internship.

A communication framework that enables multiple AI agents to collaborate through asynchronous messaging, agent registration, and discovery. It facilitates complex task coordination and real-time discussion across distributed agent workflows using the Model Context Protocol.

Validates release hygiene in local repositories with network-free, read-only tools for checking repo structure, version alignment, and generating release checklists.

Enables AI agents to safely monitor Linux VPS health, inspect Docker containers, retrieve service logs, and execute whitelisted recovery actions via MCP.

Security, cost, and health governance proxy for MCP infrastructure. Enforces YAML-configurable security policies (blocklists, rate limits, token budgets), tracks real token costs via tiktoken, monitors server health with live JSON-RPC probes. Features OAuth 2.1/OIDC with RBAC, web dashboard, payload normalization, semantic shell AST analysis, mTLS, and a formal STRIDE threat model.

Enables AI agents to manage a synthetic workforce dataset with human-in-the-loop approval required for destructive or anomalous operations, such as termination, deletion, and anomalous output logging, ensuring changes are gated until explicitly approved.

Exposes the Agentic Patterns Catalog as MCP resources and tools for AI coding agents to search, retrieve, and recommend patterns, recipes, frameworks, methodologies, and anti-patterns.