Open Source Project to help Secure LLM powered Applications

Reddit r/artificial Tools

Summary

Sente Labs open-sourced extensible-mcp, an MCP proxy that dynamically loads MCP servers without polluting the LLM context while enforcing zero-trust policy controls (Rego, CEL, and now Cedar) over tool calls. Tool definitions live in a queryable vector store, and policies and credentials are kept outside the LLM's reach, distinguishing user intent from granted rights.

We built extensible-mcp to help folks build LLM powered applications securely. From a technical perspective it is an MCP proxy capable of loading new MCP Servers dynamically without polluting the LLM’s context while providing Zero Trust policy controls to manage all tool calls. Policies and sensitive credentials are maintained and applied outside the LLMs purview. Policies can be written in any of Rego, CEL, and, with the latest release, Cedar. Tool definitions from the various MCP Servers are maintained in a queryable vector store, so the LLM only needs to be aware of those it uses. A particular distinction of extensible-mcp is distinguishing between rights and intents. If an LLM is acting on your behalf, its actions should follow your intent, and not just do any random thing you could do, just because some hallucination told it to! I hope other folks find this useful. We have been using it for our other projects such as Open Executive and wanted to share it. You can check out extensible-mcp here: https://github.com/SenteLabsAI/extensible-mcp
Original Article

Similar Articles

PrologMCP: A Standardized Prolog Tool Interface for LLM Agents

arXiv cs.AI

Introduces PrologMCP, an open-source server that exposes Prolog as a stateful tool via the Model Context Protocol, enabling LLM agents to delegate reasoning to a symbolic solver. Evaluation shows competitive or superior accuracy on deductive reasoning tasks compared to frontier reasoning LLMs.

GetMCP: Zero Trust for AI agents

Reddit r/AI_Agents

GetMCP is a self-hostable open-source tool that brings zero-trust security to AI agents by providing per-request audit, per-agent revocation, policy enforcement, and human-in-the-loop approvals for API calls. It generates MCP servers from OpenAPI specs and acts as a streaming proxy with tamper-evident audit logs.