agent-cost-allocator-mcp

v1.0.1 suspicious
5.0
Medium Risk

Agent Cost Allocator MCP — multi-tenant LLM cost attribution for chargeback billing. Companion to agent-token-budget. Splits one agent's spend across many tenants for invoicing. By MEOK AI Labs.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to its novelty and lack of maintainer history, suggesting potential supply-chain risks.

  • New package with no maintainer history
  • Lack of community engagement
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating safe handling of secrets and credentials.
  • Metadata: The package is new, lacks maintainer history, and the repository shows no community engagement.

🔬 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 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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-cost-allocator-mcp 
Create a mini-application named 'TenantBillingSystem' using Python that leverages the 'agent-cost-allocator-mcp' package to manage costs for multiple tenants who share a single large language model (LLM) service. This system will help in accurately attributing costs to each tenant based on their usage of the shared LLM service, which is crucial for chargeback billing.

Step 1: Define the application structure.
- Initialize a new Python virtual environment.
- Install necessary packages including 'agent-cost-allocator-mcp'.

Step 2: Design the database schema.
- Use SQLite as the backend database.
- Create tables for tenants, services, and transactions.

Step 3: Implement the cost allocation logic.
- Utilize 'agent-cost-allocator-mcp' to calculate the cost attributed to each tenant based on their usage.
- Ensure the cost calculation takes into account different pricing tiers for various services.

Step 4: Develop the user interface.
- Create a simple web interface using Flask or Django.
- Provide functionality for adding new tenants, managing services, and viewing transaction details.

Step 5: Integrate third-party APIs.
- Optionally, integrate with payment gateways like Stripe to handle automated billing.
- Include support for API keys for secure access control.

Suggested Features:
- Real-time cost tracking for each tenant.
- Historical cost reports and analytics.
- Automatic invoicing and payment reminders.
- Role-based access control for administrators and tenants.
- Integration with popular LLM services like Anthropic Claude or OpenAI models.