Install
$ agentstack add mcp-awslabs-log-analyzer-with-mcp ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Log Analyzer with MCP
A Model Context Protocol (MCP) server that provides AI assistants access to AWS CloudWatch Logs for analysis, searching, and correlation.
🏗️ Architecture
🔌 Model Context Protocol (MCP)
As outlined by Anthropic: > MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.
This repository is an example client and server that allows an AI assistant like Claude to interact with CloudWatch logs in an AWS account. To learn more about MCP, read through the introduction.
✨ Features
- Browse and search CloudWatch Log Groups
- Search logs using CloudWatch Logs Insights query syntax
- Generate log summaries and identify error patterns
- Correlate logs across multiple AWS services
- AI-optimized tools for assistants like Claude
[Detailed feature list](./docs/features.md)
🚀 Installation
Prerequisites
- The uv Python package and project manager (includes
uvx) - An AWS account with CloudWatch Logs
- Configured [AWS credentials](./docs/aws-config.md)
🚦 Quick Start
- Make sure to have configured your AWS credentials as [described here](./docs/aws-config.md)
- Update your
claude_desktop_config.jsonfile with the proper configuration outlined in the [AI integration guide](./docs/ai-integration.md)
- Open Claude for Desktop and start chatting!
For more examples and advanced usage, see the [detailed usage guide](./docs/usage.md).
🤖 AI Integration
This project can be easily integrated with AI assistants like Claude for Desktop. See the [AI integration guide](./docs/ai-integration.md) for details.
📚 Documentation
- [Detailed Features](./docs/features.md)
- [Usage Guide](./docs/usage.md)
- [AWS Configuration](./docs/aws-config.md)
- [Architecture Details](./docs/architecture.md)
- [AI Integration](./docs/ai-integration.md)
- [Troubleshooting](./docs/troubleshooting.md)
🔒 Security
See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.
📄 License
This project is licensed under the Apache-2.0 License.
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: awslabs
- Source: awslabs/Log-Analyzer-with-MCP
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.