🌐 Enterprise Model Context Protocol (MCP) Agent Framework

An open-standard, production-grade Model Context Protocol (MCP) implementation and Multi-Server Gateway designed for enterprise agentic workflows, dynamic tool discovery, and vendor-agnostic AI orchestration.

📌 Executive Summary

Modern AI systems require seamless, reliable, and standardized communication with external software tools, databases, and enterprise workspaces. Traditional integrations suffer from brittle hardcoded bindings and proprietary vendor lock-in.

This repository implements the Model Context Protocol (MCP) — the emerging industry standard for connecting AI models to contextual tools and external APIs:

• Zero-Hardcoding: Tools are declared with strict JSON Schema definitions and discovered dynamically at runtime via /tools/list.

• Central MCP Gateway: Aggregates distributed MCP servers, manages namespacing, handles route dispatching, and exports standardized function definitions for any Large Language Model (Anthropic Claude, OpenAI, Gemini, Groq, Llama).

• Enterprise Productivity Adapters: Built-in modules for real-time web intelligence, document parsing (PDF/RAG), calendar scheduling, and email communication.

• Alignment with Digital Public Goods & Open Standards: Fully open-source, modular, and privacy-first architecture suitable for public sector organizations (e.g., United Nations, UNDP), multilateral agencies, and global enterprises.

Related MCP server: WorkplaceSearchAgent MCP Server

🏗 Architecture Overview

 ┌────────────────────────────────────────────────────────────────────────┐
 │                     LLM / AGENTIC ORCHESTRATOR                         │
 │           (OpenAI, Anthropic Claude, Gemini, Groq, Llama)              │
 └───────────────────────────────────┬────────────────────────────────────┘
                                     │ Dynamic Tool Call (JSON Schema)
                                     ▼
 ┌────────────────────────────────────────────────────────────────────────┐
 │                         MCP SERVER GATEWAY                             │
 │   - Multi-server Discovery & Schema Aggregation                        │
 │   - Namespacing & Collision Avoidance                                  │
 │   - Fault-tolerant Fallback & In-Memory Routing                        │
 └──────────────┬────────────────────────────┬────────────────────────────┘
                │ HTTP Stream / JSON-RPC     │ HTTP Stream / JSON-RPC
                ▼                            ▼
 ┌──────────────────────────────┐ ┌──────────────────────────────────────┐
 │     CORE WORKSPACE SERVER    │ │        WEB INTELLIGENCE SERVER       │
 │   - Meeting & Calendar Sync  │ │   - Live DuckDuckGo / Tavily Search  │
 │   - Email Dispatch           │ │   - Source Extraction & Verification │
 │   - Drive / Document Parsing │ └──────────────────────────────────────┘
 └──────────────────────────────┘

🛠 Key Capabilities

🚀 Quickstart in 60 Seconds

1. Clone & Set Up Environment

# Clone the repository
git clone https://gitlab.com/your-username/mcp-agent-showcase.git
cd mcp-agent-showcase

# Create and activate virtual environment
python -m venv .venv
# On Linux/macOS: source .venv/bin/activate
# On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

2. Run the Interactive End-to-End Demo

Execute the self-contained demonstration script:

python quickstart_demo.py

This script automatically:

1. Spawns the MCP Server in the background.

2. Initializes the MCP Gateway and discovers published tools dynamically.

3. Generates the exact JSON Schemas used for LLM Function Calling.

4. Executes a full 4-step automated agentic workflow (Web Search ➔ Document Parsing ➔ Meeting Scheduling ➔ Email Confirmation).

📦 Project Structure

mcp-agent-showcase/
├── mcp_server.py           # Core MCP Server (FastMCP / JSON-RPC endpoints)
├── mcp_gateway.py          # Central Gateway aggregating multiple MCP servers
├── quickstart_demo.py      # End-to-end multi-step workflow demonstration
├── requirements.txt        # Minimal, clean Python dependencies
├── .env.example            # Configuration template
├── LICENSE                 # Apache 2.0 Open Source License
├── tools/                  # Standardized tool adapters
│   ├── __init__.py
│   ├── web_search.py       # DuckDuckGo search integration
│   ├── document_parser.py  # Text and PDF extractor for RAG
│   └── workspace_tools.py  # Email, Calendar, Drive & Sheets adapters
└── tests/                  # Automated verification suite
    ├── __init__.py
    └── test_mcp_gateway.py # Gateway and tool schema validation tests

🧪 Testing & Verification

Run automated test suites using pytest:

pytest tests/ -v

All tool schemas, parameter validation, and gateway registry mappings are verified to ensure deterministic execution.

🌍 Strategic Relevance for Multilateral Agencies (e.g., UNDP)

• Open Standards & Digital Public Goods: Fully compliant with open protocol definitions, preventing dependence on proprietary walled gardens.

• Administrative Automation: Streamlines reporting, multi-stakeholder meeting scheduling, and document synthesis.

• Security & Transparency: Deterministic JSON Schemas provide auditable boundaries for AI tool execution, enabling human-in-the-loop oversight.

📄 License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.