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ADR MCP Server

uber/ADR

Score: 80.2 → 0% Rank #1921 Monitoring
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ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed at Uber.

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Overview

uber/ADR is a Python tool licensed under Apache-2.0. ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed at Uber. Topics: agent-security, ai-agents, ai-security, benchmark, llm-security, mcp, model-context-protocol, prompt-injection, threat-detection, claude, claude-code, codex, cursor.

Ranked #1921 out of 24846 indexed tools.

In the top 8% of all indexed tools.

Has 2,020 GitHub stars.

Has 18 contributors.

Ecosystem

Python Apache-2.0 589 pypi/wk
agent-securityai-agentsai-securitybenchmarkllm-securitymcpmodel-context-protocolprompt-injectionthreat-detectionclaudeclaude-codecodexcursor

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 2,020

2,020 stars → well-known project

Freshness 25% 29d ago

Last commit 29d ago → recently updated

Issue Health 25% 50%

16/32 issues closed → decent issue management

Contributors 10% 18

18 contributors → active community

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads 13% 589/wk

589 weekly installs → early adoption

Forks 214
Description Good
License Apache-2.0

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

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Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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AgentRank score for uber/ADR
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Matched Queries

topic:mcptopic:model-context-protocol

From the README

# ADR: Agentic AI Detection and Response

ADR (Agentic AI Detection and Response) is an enterprise security system for AI agents. It helps organizations secure employee-facing agents such as Cursor, Claude Code, Codex, GitHub Copilot CLI, and DeepSeek Harness, as well as customer-facing agents such as AI support agents.

ADR is **deployed in production at Uber**, and the accompanying paper was accepted to **MLSys 2026**: [Paper PDF](docs/adr-paper.pdf) · [Slides PDF](docs/adr-mlsys-2026-slides.pdf)

## How ADR secures enterprise AI agents

ADR secures enterprise AI agents through five complementary capabilities: discovering unsanctioned AI tools, observing agent activity, evaluating defenses, detecting threats, and preventing unsafe actions.

1. **ADR Discovery: Find the AI tools present on employee endpoints.** Inventories installed AI applications, CLI agents, IDE extensions, local model runtimes, and MCP servers, and flags unknown surfaces for review.
2. **ADR Observability: Underst
Read full README on GitHub →

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