This server is fundamentally non-functional as an MCP tool provider. The source code shows only a stub implementation that prints a JSON initialization message and exits. There is exactly ONE tool declared: 'execute_skill_action'. However, the tool has NO input schema visible in the source, NO parameter descriptions, and NO output schema documentation. The description states the tool is 'declared in server tool list but not implemented in provided source', meaning the tool definition exists only nominally, without any actual implementation or schema. The client.py and example_usage.py files are unrelated utility code that do not register tools with the MCP server. This is a non-starter for production use.

• Implement a complete MCP request/response loop in mcp_server.py. Start with the MCP Python SDK or reference the MCP specification. The server must listen for incoming JSON-RPC 2.0 requests on stdin and write responses to stdout.
• Define a complete JSON Schema for execute_skill_action's input parameters. Include parameter names, types (string, number, boolean, object, array), descriptions, enums for constrained values, and any min/max bounds. Example: { "type": "object", "properties": { "action": { "type": "string", "description": "The skill action to execute", "enum": ["analyze", "predict", "engage"] } }, "required": ["action"] }
• Add a comprehensive description to execute_skill_action. Follow the pattern: 'Execute a skill action from the social intelligence plugin. Supported actions include: analyze (analyze social context), predict (predict agent behavior), engage (generate engagement suggestions). Returns a result object with action_status, output_data, and any errors.' Keep between 50 - 200 characters for clarity.
• Document the output schema for execute_skill_action. Specify what fields are returned (e.g., action_status: string, output_data: object, error: string or null) and their types.
• Integrate the AgentSocialIntelligencePluginClient class into the MCP server's tool handler so that execute_skill_action invocations actually call the client methods. Currently, the client is standalone utility code unconnected to the server.
• Add error handling. Return structured error responses with actionable guidance: 'Invalid action: got "unknown", must be one of: analyze, predict, engage.' Categorize errors as retryable or fatal.