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Debby McKinney
Debby McKinney

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Top 5 MCP Gateways for Building Production AI Agents

You're building an AI agent that needs to read files, search the web, and query your database. Model Context Protocol (MCP) standardizes how agents discover and use these tools.

But you quickly discover that running MCP servers directly in production creates problems: no observability into what tools your agents actually use, no security controls over dangerous operations, and no centralized way to manage dozens of tool integrations.

MCP gateways solve these problems. This post compares the top 5 solutions based on performance, security, and ease of use.


Why You Need an MCP Gateway

Running MCP servers without a gateway works for demos. Production needs:

Security: Your MCP server can execute arbitrary code. Without a gateway, every agent has full access to every tool. No granular permissions, no audit trail, no way to restrict dangerous operations.

Observability: Direct MCP connections give you zero visibility. You can't see which tools got called, how long they took, or how much they cost. Debugging failures becomes guesswork.

Management: Each agent manages its own MCP server connections. This works with 2-3 tools. At 20+ tools across multiple environments, manual configuration becomes unmanageable.

Gateways centralize security, observability, and management at the infrastructure level.


1. Bifrost by Maxim AI

GitHub logo maximhq / bifrost

Fastest LLM gateway (50x faster than LiteLLM) with adaptive load balancer, cluster mode, guardrails, 1000+ models support & <100 µs overhead at 5k RPS.

Bifrost

Go Report Card Discord badge Known Vulnerabilities codecov Docker Pulls Run In Postman Artifact Hub License

The fastest way to build AI applications that never go down

Bifrost is a high-performance AI gateway that unifies access to 15+ providers (OpenAI, Anthropic, AWS Bedrock, Google Vertex, and more) through a single OpenAI-compatible API. Deploy in seconds with zero configuration and get automatic failover, load balancing, semantic caching, and enterprise-grade features.

Quick Start

Get started

Go from zero to production-ready AI gateway in under a minute.

Step 1: Start Bifrost Gateway

# Install and run locally
npx -y @maximhq/bifrost

# Or use Docker
docker run -p 8080:8080 maximhq/bifrost
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Step 2: Configure via Web UI

# Open the built-in web interface
open http://localhost:8080
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Step 3: Make your first API call

curl -X POST http://localhost:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-4o-mini",
    "messages": [{"role": "user", "content": "Hello, Bifrost!"}]
  }'
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That's it! Your AI gateway is running with a web interface for visual configuration, real-time monitoring…

What it is: High-performance MCP gateway built in Go with comprehensive tool management and observability.

Performance: Sub-3ms latency, 350+ requests/second per core

Why it's fast: Built in Go (compiled language), not Python. Native concurrency, minimal memory overhead, no interpreter.

Key MCP features:

  • Connect to any MCP server via STDIO, HTTP, or SSE
  • Agent mode: autonomous tool execution with configurable auto-approval
  • Code mode: AI writes TypeScript to orchestrate multiple tools
  • Expose Bifrost as MCP server for Claude Desktop
  • Filter tools per-request, per-user, or per-virtual-key

Security approach:

By default, tool calls are suggestions only. Execution requires explicit API call. This "explicit execution" model prevents accidental dangerous operations.

Enable auto-execution for specific tools:

{
  "tools_to_auto_execute": ["web_search", "file_read"]
}
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Risky tools (database writes, file deletions) require manual approval.

Setup:

npx -y @maximhq/bifrost
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Configure MCP servers via web UI at http://localhost:8080 or edit config.json:

{
  "mcp": {
    "servers": [
      {
        "name": "filesystem",
        "command": "npx",
        "args": ["-y", "@modelcontextprotocol/server-filesystem", "/allowed/path"],
        "type": "stdio"
      }
    ]
  }
}
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Observability:

  • Built-in dashboard shows tool execution in real-time
  • Prometheus metrics at /metrics
  • OpenTelemetry distributed tracing
  • Cost tracking per tool

Best for: You need sub-3ms latency, want comprehensive observability, and don't want to spend days configuring security policies.

Docs:

Setting Up - Bifrost

Get Bifrost running as an HTTP API gateway in 30 seconds with zero configuration. Perfect for any programming language.

favicon docs.getbifrost.ai

2. TrueFoundry

What it is: AI infrastructure platform with MCP gateway built-in.

Performance: 3-4ms latency, 350+ RPS per core

What makes it different: TrueFoundry isn't just an MCP gateway. It's a complete AI infrastructure platform that also manages models, deployments, and monitoring.

Key features:

  • MCP server management and deployment
  • Model deployment and versioning
  • Unified observability across models and tools
  • Multi-environment support (dev, staging, prod)

Best for: You want single platform managing both your models AND your tools. You're willing to adopt TrueFoundry's broader infrastructure.


3. IBM Context Forge

What it is: Enterprise MCP federation for large organizations.

Performance: 100-300ms latency (depends on configuration)

What makes it different: Designed for enterprises with 10,000+ employees needing complex multi-tenant governance.

Key features:

  • Federation across multiple MCP server deployments
  • Enterprise governance and compliance
  • Complex routing and policy enforcement
  • Multi-tenant isolation

Trade-offs:

  • 100-300ms latency (vs sub-3ms alternatives)
  • Difficult integration (no official support)
  • High operational complexity

Best for: You're a large enterprise requiring federated MCP governance across multiple business units. Latency is acceptable tradeoff for governance features.


4. Microsoft MCP Gateway

What it is: Azure-native MCP gateway with deep Microsoft ecosystem integration.

Performance: 80-150ms latency, cloud-limited concurrency

What makes it different: Built specifically for Azure. If you're already on Azure, integration is seamless.

Key features:

  • Deep Azure integration
  • Cloud-managed infrastructure
  • Azure AD authentication
  • Enterprise compliance features

Trade-offs:

  • 80-150ms latency
  • Azure vendor lock-in
  • Complex management interface

Best for: You're already on Azure and want native MCP support without managing your own infrastructure.


5. Lasso Security

What it is: Security-focused MCP gateway with comprehensive threat detection.

Performance: 100-250ms latency (security overhead)

What makes it different: Security-first design. Every tool execution monitored for threats, jailbreaks, and data exfiltration.

Security features:

  • Real-time threat detection for AI agents
  • Tool reputation analysis (tracks MCP server behavior)
  • Jailbreak monitoring
  • Data exfiltration detection
  • Detailed audit trails for compliance

Trade-offs:

  • 100-250ms latency overhead
  • High memory usage
  • Security adds operational complexity

Best for: You're in healthcare, finance, or other regulated industry requiring comprehensive security monitoring and audit trails.


Performance Reality Check

Latency matters when your agent makes multiple tool calls.

Example: Agent making 50 tool calls per interaction

  • Bifrost: 50 × 3ms = 150ms total overhead
  • TrueFoundry: 50 × 3ms = 150ms total overhead
  • Microsoft: 50 × 80ms = 4 seconds total overhead
  • IBM Context Forge: 50 × 100ms = 5 seconds total overhead
  • Lasso Security: 50 × 100ms = 5 seconds total overhead

Sub-3ms latency eliminates the gateway from your latency budget. 100ms+ latency makes it the bottleneck.


Quick Comparison

Gateway Latency Setup Integration Security Best For
Bifrost <3ms Very Easy Drop-in Granular Performance + ease of use
TrueFoundry 3-4ms Easy Platform Standard Unified AI infrastructure
IBM Context Forge 100-300ms Difficult Complex Enterprise Large enterprise federation
Microsoft 80-150ms Medium Azure-only Azure-native Azure ecosystem
Lasso Security 100-250ms Medium Moderate Comprehensive Regulated industries

How to Choose

Start with Bifrost if you need production-ready performance (sub-3ms), comprehensive observability, and want to get running in under 5 minutes. It's the fastest option and requires zero configuration to start.

Choose TrueFoundry if you want single platform for models and tools. Good if you're already adopting their infrastructure.

Choose IBM Context Forge if you're a large enterprise (10,000+ employees) requiring complex multi-tenant MCP governance. Accept higher latency and complexity for enterprise features.

Choose Microsoft if you're all-in on Azure and willing to accept 80-150ms latency for native integration.

Choose Lasso Security if you're in a regulated industry and need comprehensive security monitoring. The latency overhead is acceptable when compliance requires detailed audit trails.

Top comments (1)

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javz profile image
Julien Avezou

Nice breakdown of MCP Gateways, I appreciate the comparison table! I will bookmark this for later for my projects.