Model Context Protocol (MCP) Server for AI Data Privacy: LLM prompt firewall, audit logs, and 74 MCP tools for Claude, Codex, Cursor, and Windsurf.
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<div align="center"> # ⚡ AgenticStore MCP Server: LLM Prompt Firewall, Token Optimization & AI Security Toolkit **Open-source Model Context Protocol (MCP) server for data privacy, prompt recording, audit logs, Relay project delivery, and 74 tools for Claude Code, Codex, Cursor, and Windsurf.** [](https://opensource.org/licenses/MIT) [](https://www.python.org/downloads/) [](https://modelcontextprotocol.io) [](https://pypi.org/project/agentic-store-mcp/) [Documentation](https://agenticstore.dev/docs) • [Quick start](#-quick-start-guide-fastest-way-to-install) • [Prompt Firewall](#%EF%B8%8F-llm-prompt-firewall--sanitization) • [Relay](#-relay-jira-for-ai-agents) • [Tool directory](#-tool-directory--all-74-tools) • [Client setup](#-connect-to-your-ai-client) • [GUI webapp](https://agenticstore.dev/docs/gui) </div> --- ## 🔒 Why You Need This: Enterprise-Grade AI Security Meets Autonomous Agents Giving AI assistants like **Claude, Cursor, and Windsurf** access to your codebase and the web is a superpower. But passing sensitive enterprise data to remote LLMs is a massive security risk. Furthermore, hitting token limits quickly degrades LLM context windows and increases costs. **The Problem:** You want the massive productivity boost of agentic workflows, but you cannot compromise on Data Loss Prevention (DLP), compliance, leak prevention, or token bloat. **The Solution:** AgenticStore MCP Server solves the entire equation natively: * 🛡️ **The LLM Prompt Firewall:** A secure local proxy that intercepts, scans, and sanitizes your prompts *before* they leave your machine. It flags leaked secrets, PII, and API keys, us…
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