Enterprise AI Toolkit MCP
README.md
# Enterprise AI Toolkit MCP
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> An enterprise MCP server that exposes reusable AI, RAG, document intelligence, knowledge graph, SQL, evaluation, and AI architecture capabilities as standardized tools for AI agents.
---
## 🌟 Vision & Overview
The **Enterprise AI Toolkit MCP** acts as an enterprise capability gateway between AI agents (Claude, Gemini, OpenAI, custom agents) and backend enterprise AI infrastructure. Instead of coupling an agent to monolithic custom code or fragile API calls, agents can discover and compose standardized tools for document processing, RAG research, knowledge graph queries, natural language SQL, model evaluation, and cloud architecture design.
```text
┌───────────────────────┐
│ AI Agent │
│ Claude / Gemini / │
│ OpenAI / Custom Agent │
└───────────┬───────────┘
│
│ MCP JSON-RPC
▼
┌──────────────────────────────┐
│ Enterprise AI Toolkit MCP │
│ │
│ MCP Server + Tool Registry │
└──────────────┬───────────────┘
│
┌────────────────────────┼────────────────────────┐
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Document Tools │ │ Knowledge Tools │ │ Data Tools │
├─────────────────┤ ├─────────────────┤ ├─────────────────┤
│ OCR & Extract │ │ Vector Search │ │ SQL Generation │
│ Summarization │ │ Grounded RAG │ │ SQL Validation │
│ Contract Audit │ │ Knowledge Graph │ │ Execute Query │
└─────────────────┘ └─────────────────┘ └─────────────────┘
┌────────────────────────┼────────────────────────┐
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ LLM Tools │ │ Evaluation │ │ Architecture │
├─────────────────┤ ├─────────────────┤ ├─────────────────┤
│ LLM Evaluation │ │ Faithfulness │ │ AI Architecture│
│ Cost Estimator │ │ Groundedness │ │ TCO Cost Calc │
│ Prompt Guard │ │ Latency & Cost │ │ Tech Stack │
└─────────────────┘ └─────────────────┘ └─────────────────┘
```
---
## 🚀 Key Features
* **16 Standardized MCP Tools**: Complete coverage for Document Intelligence, RAG, Knowledge Graph, SQL Intelligence, LLM Evaluation, Cost Estimation, and Cloud Architecture.
* **100% Demo Mode / Zero API Key Requirement**: Runs out of the box using intelligent offline `MockLLMProvider`, local vector index, in-memory Knowledge Graph, and SQLite database.
* **LLM Provider Agnostic**: Easily toggle between Google Gemini (`gemini-2.5-flash`), OpenAI (`gpt-4o-mini`), and local mock provider.
* **Enterprise Security & Governance**:
* `PromptGuard`: Prompt injection threat detection and token efficiency analysis.
* `SQLGuard`: Enforces read-only execution, blocks multi-statements, and catches dangerous keywords (`DROP`, `DELETE`, `TRUNCATE`).
* `InputValidator`: Path traversal protection and upload size guards.
* **MCP Resources & Prompts**: Exposes `resource://enterprise-ai/catalog`, `configuration`, `model-registry`, `tool-metrics`, and standardized prompts (`enterprise_rag_analysis`, `enterprise_sql_analysis`, `enterprise_contract_review`, `enterprise_ai_architecture`).
---
## 🛠️ MCP Tools Reference
| Category | Tool Name | Description | Risk Level |
|---|---|---|---|
| **Documents** | `extract_document` | Extracts text, pages, metadata, headings, and chunks | LOW |
| **Documents** | `summarize_document` | Generates executive summaries, key takeaways, and action items | LOW |
| **Documents** | `analyze_contract` | Audits legal contracts for terms, obligations, risks, and risk score | MEDIUM |
| **Knowledge** | `search_knowledge` | Semantic vector search over enterprise document chunks | LOW |
| **Knowledge** | `generate_rag_answer` | Grounded RAG research with source citations | LOW |
| **Knowledge** | `query_knowledge_graph` | Queries and traverses entity-relationship Knowledge Graph | LOW |
| **Data** | `generate_sql` | Translates natural language into safe SQL queries | MEDIUM |
| **Data** | `validate_sql` | Validates SQL syntax against security policies and injection | LOW |
| **Data** | `execute_sql` | Safely executes read-only SQL queries against database | MEDIUM |
| **Data** | `analyze_database_schema` | Inspects database schema, foreign keys, and optimization tips | LOW |
| **LLM** | `evaluate_llm` | Evaluates LLM responses across correctness, relevance, faithfulness | LOW |
| **LLM** | `estimate_llm_cost` | Estimates daily, monthly, and annual LLM pricing | LOW |
| **LLM** | `analyze_prompt` | Analyzes prompt for security risks and injection threats | LOW |
| **LLM** | `recommend_llm` | Recommends optimal LLM based on budget, latency, and privacy | LOW |
| **Architecture** | `design_ai_architecture` | Generates enterprise AI architecture design with Mermaid diagram | LOW |
| **Architecture** | `estimate_ai_solution_cost` | Calculates TCO for enterprise GenAI solution | LOW |
---
## 💻 Quick Start & Installation
### 1. Install local package
```bash
pip install -e .
```
### 2. Run CLI commands
```bash
# List all 16 registered tools
enterprise-ai-mcp list-tools
# Check server health
enterprise-ai-mcp health
# Run E2E BFSI Demo Workflow
enterprise-ai-mcp demo
```
### 3. Run MCP Server in stdio mode
```bash
enterprise-ai-mcp server --transport stdio
```
---
## 🧪 Testing
The repository includes a unit and integration test suite runnable without external API keys:
```bash
python -m pytest
```
---
## 🐳 Docker Deployment
```bash
# Docker Compose
docker-compose up -d
# Docker CLI
docker build -t enterprise-ai-mcp .
docker run -p 8000:8000 enterprise-ai-mcp
```
---
## 📝 License
Distributed under the [MIT License](./LICENSE).
This server cannot be deployed
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