Overview

What is MCP?

Model Context Protocol (MCP) is an open standard that enables AI models to seamlessly discover and execute external tools at runtime. Instead of being limited to text generation, AI models can interact with filesystems, search the web, query databases, and execute custom business logic through external MCP servers.

DeepIntShield provides a comprehensive MCP integration that goes beyond simple tool execution:

• MCP Client: Connect to any MCP-compatible server (filesystem tools, web search, databases, etc.)
• MCP Server: Expose your connected tools to external MCP clients (like Claude Desktop)
• Agent Mode: Autonomous tool execution with configurable auto-approval
• Code Mode: Let AI write and execute Python to orchestrate multiple tools

Security-First Design

Note

By default, DeepIntShield does NOT automatically execute tool calls. All tool execution requires explicit API calls, ensuring human oversight for potentially dangerous operations. However, you can enable Agent Mode to allow automatic execution of specific tools via the tools_to_auto_execute configuration.

Key Security Principles:

Principle	Description
Explicit Execution	Tool calls from LLMs are suggestions only - execution requires separate API call
Granular Control	Filter tools per-request, per-client, or per-virtual-key
Opt-in Auto-execution	Agent mode with auto-execution must be explicitly configured
Stateless Design	Each API call is independent - your app controls conversation state

Key Capabilities

Connect to MCP Servers

Connect to external MCP servers via STDIO, HTTP, or SSE protocols with automatic retry logic

Open →

OAuth Authentication

Secure OAuth 2.0 authentication with automatic token refresh

Open →

Tool Execution

Execute tools with full control over approval and conversation flow

Open →

Agent Mode

Enable autonomous tool execution with configurable auto-approval

Open →

Code Mode

Let AI write Python to orchestrate multiple tools in one request

Open →

Connection Resilience

Automatic exponential backoff retry logic handles transient failures gracefully

Open →

MCP Gateway URL

Expose DeepIntShield as an MCP server for Claude Desktop and other clients

Open →

Tool Hosting

Register custom tools directly in your Go application

Open →

Tool Filtering

Control which tools are available per request or per virtual key

Open →

How MCP Works in DeepIntShield

DeepIntShield acts as both an MCP client (connecting to external tool servers) and optionally as an MCP server (exposing tools to external clients like Claude Desktop).

graph TB
    App["<b>Your Application</b>"]
    Gateway["<b>DeepIntShield Gateway</b><br/>MCP Client | MCP Server<br/>Tool Filtering & Agent Mode"]
    Servers["<b>MCP Servers</b><br/>filesystem, web search,<br/>databases, etc."]
    Clients["<b>MCP Clients</b><br/>Claude Desktop,<br/>other apps"]

    App -->|Connect| Gateway
    Gateway -->|Connect to| Servers
    Clients -->|Connect to| Gateway

    style App fill:#E3F2FD,stroke:#0D47A1,stroke-width:2.5px,color:#1A1A1A
    style Gateway fill:#E8F5E9,stroke:#1B5E20,stroke-width:2.5px,color:#1A1A1A
    style Servers fill:#FFF3E0,stroke:#BF360C,stroke-width:2.5px,color:#1A1A1A
    style Clients fill:#F3E5F5,stroke:#4A148C,stroke-width:2.5px,color:#1A1A1A

For detailed architecture information, see the MCP Architecture documentation.

Basic Tool Calling Flow

The default tool calling pattern in DeepIntShield is stateless with explicit execution:

1. POST /v1/chat/completions
   → LLM returns tool call suggestions (NOT executed)

2. Your app reviews the tool calls
   → Apply security rules, get user approval if needed

3. POST /v1/mcp/tool/execute
   → Execute approved tool calls explicitly

4. POST /v1/chat/completions
   → Continue conversation with tool results

This pattern ensures:

• No unintended API calls to external services
• No accidental data modification or deletion
• Full audit trail of all tool operations
• Human oversight for sensitive operations

Why Code Mode Matters

If you’re planning to use 3+ MCP servers, read the Code Mode documentation carefully.

Code Mode reduces token usage by 50%+ and execution latency by 40-50% compared to classic MCP by having the AI write Python code to orchestrate tools in a sandbox, rather than exposing 100+ tool definitions directly to the LLM.

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Next Steps

Connect to MCP Servers

Set up your first MCP client connection →

Choose Authentication (if needed)

Learn about header-based and OAuth 2.0 authentication →

Enable Code Mode (for 3+ servers)

Learn how Code Mode reduces costs by 50% →

Execute Tools

Learn the tool execution workflow →

Enable Agent Mode

Configure autonomous tool execution →