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"A sandbox environment to run Python code and install dependencies" matching MCP servers:

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    A secure MCP server example that demonstrates how to deploy to Google Cloud Run with authentication and identity token protection. Serves as a tutorial template for building production-ready MCP servers in the cloud.
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    An MCP server that exposes a 216-rule Kotlin/JVM security analyzer to AI coding agents, enabling real-time security scanning and secure pattern retrieval for frameworks like Spring and Ktor.
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    MIT
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    A security filter that blocks dangerous code patterns by comparing normalized structural syntax trees against a blacklist of known threats using vector embeddings. It acts as a gatekeeper to prevent malicious code execution by identifying dangerous structures regardless of specific identifiers or literals.
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    MIT
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    Enables comprehensive security vulnerability scanning and code quality analysis for Python applications. Provides detailed reports with scoring, actionable suggestions, and comparison tracking specifically designed for backend developers working with frameworks like Django, Flask, and FastAPI.
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    Talk to Okta IGA like you talk to a coworker. Import access data, discover patterns, and create entitlement bundles—all through natural conversation.
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    MIT
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    Provides secure execution of arbitrary JavaScript code within a sandboxed QuickJS WASM environment, allowing language models or other MCP clients to safely run JavaScript code snippets without compromising the host system.
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    Counterparty risk scoring for agentic commerce. Scores wallets, domains, IPs, and companies 0-100 before AI agents transact via x402 micropayments on Base
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    MIT
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    CodeSafer is an MCP server that scans AI-generated code for 9 categories of hidden security threats — including invisible Unicode, Trojan Source, homoglyphs, and rules file backdoors — using static analysis plus CodeBERT deep learning. Runs locally, free tier available.
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    Free email for AI agents with hardware attestation, real SMTP/IMAP/JMAP, and real-time notifications.
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    Apache 2.0
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    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.
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    Project Point One Percent - Agent Pay \[pop-pay] is a payment guardrail and one-time flow protocol specifically designed for Agentic AI (e.g., Claude Code, OpenClaw). It enables agents to handle financial transactions safely without risking unlimited exposure of human-controlled credit cards.
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    MIT