# Feature Idea: FastMCP Java Wrapper for LinkedIn SSI Booster

## Overview

Implement a Java-based FastMCP (Model Context Protocol) server that wraps the core automation, curation, and explainability features of LinkedIn SSI Booster, enabling native interoperability with Java/TypeScript agent stacks and orchestration frameworks.

## Problem Statement (Project Context)

- The current tool is Python CLI-only, limiting integration with Java/TS-based agentic frameworks and enterprise orchestration systems.
- No native Java MCP server exists to expose SSI Booster features as MCP-compatible tools.
- Modern agent stacks (LangChain, FastMCP, Azure AI Studio) expect MCP-compliant HTTP/JSON interfaces for tool integration.

## Proposed Solution

- Implement a FastMCP server in Java (using the official FastMCP library) that acts as a bridge to the Python SSI Booster.
- Use REST or gRPC to call Python FastAPI endpoints or invoke CLI commands from Java.
- Expose all core SSI Booster features (generate, curate, explain, report, schedule) as MCP tool endpoints.
- Support streaming and async task handling for long-running operations.
- Add /health and /version endpoints for ops.

## Expected Benefits (Project User Impact)

- Enables seamless integration with Java/TS agentic frameworks and enterprise orchestration tools.
- Allows multi-client, real-time access to SSI Booster features from any MCP-compatible stack.
- Makes the system composable in larger AI pipelines (e.g., RAG, workflow orchestration, human-in-the-loop review).
- Opens the door to cloud deployment, multi-user access, and SaaS scenarios.

## Technical Considerations (Project Integration)

- Use FastMCP Java SDK for MCP server implementation.
- Bridge to Python via REST (FastAPI), gRPC, or process invocation (with robust error handling).
- Ensure all API calls are stateless and idempotent where possible.
- Secure endpoints with API key or OAuth2 (future phase).
- Add CORS support for web UI integration if needed.
- Ensure all external API calls (Buffer, Anthropic) respect --dry-run and error handling conventions.

## Project System Integration

- fast-mcp-java/: New Java module for FastMCP server.
- Connect to Python FastAPI server or CLI for core logic.
- requirements.txt: Document Java integration requirements.
- tests/: Add integration tests for MCP endpoints and Python bridge.
- docs/: Document MCP endpoints, bridge architecture, and usage patterns.

## Initial Scope

- MCP endpoints for generate, curate, explain, report, schedule
- /health, /version endpoints
- Java-Python bridge (REST/gRPC/CLI)
- Integration tests
- Documentation

## Success Criteria

- All core SSI Booster features are accessible via MCP endpoints with matching behavior
- MCP server passes integration tests for all endpoints
- No regression in Python CLI or API workflows
- Documentation updated for MCP usage and deployment
