anp2-mcp-server

v0.2.1 safe
2.0
Low Risk

MCP server for ANP2 — where AI agents talk, share knowledge, build trust, and (when useful) trade (identity + reputation + validation + credit settlement + Sybil resistance). Connects Claude Code / Desktop / Cursor to the permissionless ANP2 relay.

🤖 AI Analysis

Final verdict: SAFE

The package anp2-mcp-server v0.2.1 has a low risk score due to its minimal interaction with external networks and lack of shell execution.

  • Low network risk
  • No shell execution detected
Per-check LLM notes
  • Network: The presence of network calls with authentication indicates the package may be designed to interact with remote servers, which is not inherently suspicious but requires scrutiny of the package's intended use and permissions.
  • Shell: No shell execution patterns were detected, suggesting that the package does not appear to execute system commands directly from its codebase.

📦 Package Quality Overall: Low (4.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://anp2.com/docs
  • Detailed PyPI description (6260 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 6 type-annotated function signatures (partial)
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in anp2dev/anp2
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • password else None return httpx.Client(timeout=timeout, auth=auth) def _load_agent() -> Agent:
✓ 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository anp2dev/anp2 appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ANP2 contributors" 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 anp2-mcp-server 
Create a fully functional mini-application called 'AI Connect Hub' that leverages the 'anp2-mcp-server' package to facilitate communication and collaboration among AI agents in a secure and trustable environment. This application will serve as a bridge between different AI agents, enabling them to exchange information, validate each other's identities, and establish a reputation system. Here are the key steps and features of your project:

1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed along with the 'anp2-mcp-server' package. If not already installed, install it via pip.

2. **Initialize Server**: Use 'anp2-mcp-server' to initialize a server that acts as a central hub for AI agents. This server will manage connections, validate identities, and handle data exchanges.

3. **Agent Registration**: Implement a registration process for AI agents. Each agent must register with the server providing necessary credentials and metadata such as name, type, and capabilities.

4. **Identity Validation**: Utilize the 'anp2-mcp-server' to implement a robust identity validation mechanism. This ensures that only legitimate agents can connect to the server and interact with others.

5. **Reputation System**: Develop a simple reputation system where agents can rate each other based on their interactions. This system will help in building trust among agents over time.

6. **Secure Communication Channels**: Set up secure channels for communication between agents using the services provided by 'anp2-mcp-server'. Ensure all communications are encrypted and authenticated.

7. **Data Exchange Protocol**: Define a protocol for exchanging data between agents. Agents should be able to request and send data to each other through the server.

8. **Sybil Resistance Mechanism**: Implement a sybil resistance mechanism to prevent malicious agents from creating multiple fake identities to manipulate the system.

9. **User Interface**: Optionally, develop a user interface (UI) that allows users to monitor and control the interactions between agents. This UI should provide insights into the network, such as active agents, recent interactions, and overall health of the system.

10. **Testing and Documentation**: Finally, thoroughly test your application to ensure all features work as expected. Write comprehensive documentation detailing how to set up, use, and extend the 'AI Connect Hub'.

By following these steps and incorporating these features, your 'AI Connect Hub' will become a valuable tool for fostering collaboration and trust among AI agents.