Megaraptor MCP

Instructions

Implementation Reference

• src/megaraptor_mcp/tools/deployment.py:1365-1468 (handler)

  The implementation of the 'generate_api_credentials' tool which generates API client credentials for MCP connections.

  async def generate_api_credentials(
      deployment_id: str,
      client_name: str = "megaraptor_api",
      validity_days: int = 365,
  ) -> list[TextContent]:
      """Generate API client credentials for MCP connection.
  
      Creates a new API client certificate for connecting this MCP
      server to a Velociraptor deployment.
  
      Args:
          deployment_id: The deployment to generate credentials for
          client_name: Name for the API client
          validity_days: Certificate validity in days
  
      Returns:
          API credentials in Velociraptor config file format.
          IMPORTANT: Save these credentials - they can only be displayed once.
      """
      try:
          from ..deployment.security import CertificateManager, CredentialStore, StoredCredential
          from ..deployment.security.credential_store import generate_credential_id
          from ..deployment.deployers import DockerDeployer
  
          # Get deployment info
          deployer = DockerDeployer()
          info = await deployer.get_status(deployment_id)
  
          if not info:
              return [TextContent(
                  type="text",
                  text=json.dumps({
                      "error": f"Deployment not found: {deployment_id}",
                      "hint": "Use list_deployments tool to see available deployments"
                  }, indent=2)
              )]
  
          # Load certificates
          cert_manager = CertificateManager()
          bundle = cert_manager.load_bundle(deployment_id)
  
          if not bundle:
              return [TextContent(
                  type="text",
                  text=json.dumps({
                      "error": "Certificate bundle not found"
                  }, indent=2)
              )]
  
          # Generate API client config (Velociraptor format)
          import yaml
          api_config = {
              "api_url": info.api_url or info.server_url,
              "ca_certificate": bundle.ca_cert,
              "client_cert": bundle.api_cert,
              "client_private_key": bundle.api_key,
          }
  
          # Store credential metadata
          cred_store = CredentialStore()
          credential = StoredCredential(
              id=generate_credential_id(),
              name=client_name,
              credential_type="api_key",
              created_at=datetime.now(timezone.utc).isoformat(),
              expires_at=(datetime.now(timezone.utc) + timedelta(days=validity_days)).isoformat(),
              deployment_id=deployment_id,
              data={"client_name": client_name},
          )
          cred_store.store(credential)
  
          # Return config in YAML format (matches Velociraptor api_client format)
          return [TextContent(
              type="text",
              text=f"""# Velociraptor API Client Configuration
  # Generated for: {client_name}
  # Deployment: {deployment_id}
  # Expires: {credential.expires_at}
  #
  # IMPORTANT: Save this configuration - it cannot be displayed again!
  # Set VELOCIRAPTOR_CONFIG_PATH to this file to use with MCP.
  
  {yaml.dump(api_config, default_flow_style=False)}"""
          )]
  
      except ImportError as e:
          return [TextContent(
              type="text",
              text=json.dumps({
                  "error": f"Missing dependency: {str(e)}",
                  "hint": "Install required packages with: pip install megaraptor-mcp[deployment]"
              }, indent=2)
          )]
  
      except Exception:
          # Generic errors - don't expose internals
          return [TextContent(
              type="text",
              text=json.dumps({
                  "error": "Operation failed",
                  "hint": "Check deployment configuration and try again"
              }, indent=2)
          )]