agent-rate-limiter-mcp

v1.0.4 suspicious
6.0
Medium Risk

Fleet-wide shared rate limiter for A2A + multi-MCP deployments. Most MCP servers rate-limit independently — a hostile agent hitting 10 MCPs gets 10x quota. This MCP is the shared counter: every MCP checks here before allowing a call. Sliding window + concurrency grants + signed enforcement attestations. By MEOK AI Labs.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network, shell, obfuscation, and credential activities, but the metadata risk score is elevated due to the author's potential unreliability.

  • Metadata risk score of 5 out of 10 due to author inactivity and lack of repository.
  • No direct evidence of malicious activity but caution advised given the metadata concerns.
Per-check LLM notes
  • Network: No network calls detected, which is normal for a rate limiter package that likely operates locally.
  • Shell: No shell execution patterns detected, consistent with a benign package focused on rate limiting functionality.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows some red flags with an author who appears new or inactive and lacks a repository presence, indicating potential unreliability.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: meok.ai>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agent-rate-limiter-mcp 
Develop a distributed microservices application called 'ServiceGuard' that leverages the 'agent-rate-limiter-mcp' package from MEOK AI Labs to ensure rate limiting across multiple MCP (Micro Control Plane) instances. ServiceGuard will act as a centralized rate limiter for a fleet of microservices, ensuring that no single client can abuse the system by hitting different microservice instances independently. Here’s a step-by-step guide on how to build this application:

1. **Setup Environment**: Initialize a new Python project and install the 'agent-rate-limiter-mcp' package alongside Flask for developing a simple REST API that interacts with the rate limiter.

2. **Design the Architecture**: Define how your microservices will communicate with the ServiceGuard rate limiter. Each microservice will send a request to the rate limiter before processing any user requests.

3. **Implement Rate Limiting Logic**: Use the 'agent-rate-limiter-mcp' package to implement sliding window and concurrency grants to control how many requests a client can make within a certain timeframe. Ensure that the rate limiter enforces these rules consistently across all microservices.

4. **Authentication and Authorization**: Integrate a mechanism for clients to authenticate themselves when making requests. Use signed enforcement attestations provided by the 'agent-rate-limiter-mcp' package to verify the authenticity of each request.

5. **Error Handling and Logging**: Implement robust error handling and logging to capture any issues related to rate limiting violations or other errors. This will help in monitoring and troubleshooting the application.

6. **Testing and Validation**: Write tests to validate that the rate limiter works correctly under various conditions, including high concurrency and different time intervals. Use load testing tools like Apache JMeter to simulate high traffic scenarios.

7. **Deployment and Scaling**: Plan for deployment across multiple environments (development, staging, production). Consider how you will scale the rate limiter to handle increased traffic without compromising performance.

8. **Documentation**: Create comprehensive documentation detailing how to use ServiceGuard, its configuration options, and best practices for integrating it into existing microservice architectures.

This project aims to demonstrate the practical application of 'agent-rate-limiter-mcp' in real-world scenarios, providing developers with a tool to protect their microservices against malicious or abusive behavior.