MCP-SOC Middleware

MCP-SOC Middleware

Enables AI agents to interact with Splunk SIEM and TheHive SOAR through a unified MCP interface, providing 12 tools for alert triage, case management, and security operations.

Category
Visit Server

README

MCP-SOC Middleware

MCP-Based Middleware for Integrating Agentic AI with Legacy SOC Infrastructure

PMICS Batch 05 | University of Dhaka, Department of CSE
CSE-810: Project on Cyber Security
Authors: Md. Abdullah Bin Salaam (H-28) · Ovishek Pal (H-54)
Supervisor: Prof. Dr. Mamun Or Rashid


One-Command Startup

git clone https://github.com/your-org/mcp-soc-middleware.git && cd mcp-soc-middleware
cp .env.example .env          # fill in ANTHROPIC_API_KEY at minimum
docker compose up -d          # starts all 5 services

Wait ~90 seconds for Splunk and TheHive to initialise, then visit:

Service URL Default credentials
MCP Middleware API http://localhost:8000/docs Bearer: mcp-dev-token-change-me-in-production-abc123
Splunk Web UI http://localhost:8001 admin / changeme123!
TheHive http://localhost:9000 admin@thehive.local / secret
Cortex http://localhost:9001 (first-run wizard)
Elasticsearch http://localhost:9200 (no auth in dev)

Architecture

┌─────────────────────────────────────────────────────┐
│                   AI Agent Layer                     │
│         (SOCOrchestrator + Anthropic Claude)         │
└───────────────────────┬─────────────────────────────┘
                        │  MCP  (Bearer Token)
┌───────────────────────▼─────────────────────────────┐
│          MCP Unified Access Layer  :8000             │
│   FastAPI · ToolRegistry · AuditLog · RateLimit      │
└──────────┬────────────────────────┬─────────────────┘
           │                        │
┌──────────▼──────────┐  ┌──────────▼──────────────┐
│   SplunkAdapter     │  │   TheHiveAdapter         │
│  5 MCP tools        │  │  7 MCP tools             │
└──────────┬──────────┘  └──────────┬───────────────┘
           │                        │
┌──────────▼──────────┐  ┌──────────▼──────────────┐
│  Splunk Enterprise  │  │  TheHive 5 + ES 7        │
│  REST API :8089     │  │  REST API :9000          │
└─────────────────────┘  └─────────────────────────┘

Project Structure

mcp-soc-middleware/
├── mcp_server/                  # FastAPI MCP server package
│   ├── main.py                  # App factory, lifespan, MCP endpoints
│   ├── core/
│   │   ├── registry.py          # Dynamic tool registry and adapter loader
│   │   └── auth.py              # Bearer token authentication dependency
│   ├── adapters/
│   │   ├── base_adapter.py      # Abstract adapter contract
│   │   ├── splunk_adapter.py    # Splunk SIEM adapter (5 tools)
│   │   └── thehive_adapter.py   # TheHive SOAR adapter (7 tools)
│   ├── middleware/
│   │   ├── audit.py             # JSONL audit logging middleware
│   │   └── rate_limit.py        # slowapi rate limiter
│   ├── models/
│   │   ├── tool_models.py       # MCP ToolDefinition, Request, Response models
│   │   └── alert_models.py      # Normalised alert / observable schemas
│   └── utils/                   # (extensible — logging helpers, etc.)
│
├── agent/
│   ├── orchestrator.py          # ReAct loop + MCP client + Anthropic API
│   ├── workflows/
│   │   └── triage_workflow.py   # Pre-built task strings for common workflows
│   └── prompts/                 # (extensible — prompt template files)
│
├── config/
│   └── settings.py              # Pydantic-Settings configuration model
│
├── tests/
│   ├── unit/adapters/
│   │   ├── test_splunk_adapter.py
│   │   └── test_thehive_adapter.py
│   ├── integration/             # (full end-to-end tests against live services)
│   └── fixtures/                # Shared test data and factory-boy factories
│
├── scripts/
│   ├── bootstrap.sh             # One-time local setup (venv + .env)
│   └── splunk_bootstrap.sh      # Generate Splunk API token post-startup
│
├── docker/
│   ├── Dockerfile               # Multi-stage image for mcp-middleware service
│   ├── splunk/
│   │   ├── inputs.conf          # Splunk monitor stanza for sample data
│   │   └── sample_alerts.json   # Synthetic SOC alerts for dev seeding
│   └── thehive/
│       └── application.conf     # TheHive minimal config pointing to ES
│
├── logs/                        # Audit JSONL logs (git-ignored)
├── docs/                        # Architecture diagrams and runbooks
├── docker-compose.yml           # Full local dev stack (5 services)
├── requirements.txt             # Pinned Python dependencies
├── pyproject.toml               # Build config, ruff, mypy, pytest settings
├── .env.example                 # All required environment variables with defaults
└── README.md                    # This file

Local Development (without Docker)

# 1. Bootstrap virtual environment
bash scripts/bootstrap.sh
source .venv/bin/activate

# 2. Start only the platform dependencies via Docker
docker compose up -d splunk elasticsearch thehive

# 3. Generate a Splunk API token (first time only)
bash scripts/splunk_bootstrap.sh
# → Paste the printed token into .env as SPLUNK_TOKEN=...

# 4. Run the MCP server
python -m mcp_server.main
# Server starts at http://localhost:8000

# 5. In a separate terminal: run the AI agent on a triage task
python - <<'EOF'
import asyncio
from agent.orchestrator import SOCOrchestrator
from agent.workflows.triage_workflow import alert_triage_task

async def main():
    agent = SOCOrchestrator()
    result = await agent.run(alert_triage_task(time_window="-4h", severity="high"))
    print(result)

asyncio.run(main())
EOF

Running Tests

pytest                          # all tests with coverage
pytest tests/unit -v            # unit tests only (no live services needed)
pytest tests/integration -v     # requires docker compose up -d

MCP API Reference

All endpoints require Authorization: Bearer <MCP_BEARER_TOKEN>.

GET /tools/list

Returns the full tool catalogue (12 tools across Splunk + TheHive adapters).

POST /tools/call

{
  "name": "splunk.search_alerts",
  "arguments": {
    "severity": "high",
    "earliest": "-4h",
    "limit": 50
  }
}

Available Tools

Tool Platform Description
splunk.search_alerts Splunk Search notable events by severity/time
splunk.get_alert_details Splunk Full field set for one event ID
splunk.search_events Splunk Arbitrary SPL query
splunk.get_index_summary Splunk Available indexes and sourcetypes
splunk.acknowledge_notable Splunk Update notable event status/owner
thehive.create_case TheHive Create a new case
thehive.get_case TheHive Retrieve case by ID
thehive.list_cases TheHive List cases by status/severity
thehive.create_alert TheHive Create an alert from external data
thehive.add_observable TheHive Add IP/domain/hash/URL to a case
thehive.update_case_status TheHive Update status and add summary note
thehive.add_task TheHive Create an analyst task inside a case

Extending with a New Adapter

  1. Create mcp_server/adapters/my_tool_adapter.py inheriting BaseAdapter.
  2. Implement register_tools() returning your ToolDefinition list.
  3. Expose module-level register_tools(), adapter_setup(), adapter_teardown() functions.
  4. Add the module path to ADAPTER_MODULES in mcp_server/main.py.

No changes to the registry, middleware, or AI agent are required.


Environment Variables

See .env.example for the full annotated list. Minimum required for local dev:

ANTHROPIC_API_KEY=sk-ant-api03-...   # required for AI agent
MCP_BEARER_TOKEN=...                  # any strong random string
SPLUNK_TOKEN=...                      # from scripts/splunk_bootstrap.sh
THEHIVE_API_KEY=...                   # from TheHive UI → Admin → Users

License

MIT © 2026 Md. Abdullah Bin Salaam & Ovishek Pal

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured