MCP100 verdict
Not currently recommended. AI gateway/control plane that can act as an MCP client and server and apply access controls around MCP tools. Capabilities: Connect to upstream MCP servers; Expose MCP capabilities through Bifrost; Apply role/virtual-key/tool scoping and gateway controls; Use OAuth2 and gateway telemetry/audit features documented by Bifrost
MCP100 Assessment
Editorial verdict
Reviewed September 13, 2026
Task Fit
Mapped
Cloud operations
Trust
Status warning
maintenance_source_health; install_supply_chain; advisory_freshness; adoption_evidence_presence; resource_type_requirements
Maintenance
Recheck needed
The source snapshot needs another refresh before maintenance can be interpreted.
Popularity
Signals unavailable
No independently comparable adoption metric is currently stored.
Evidence scope
No MCP-specific repository metric is stored
No MCP-specific package metric is stored
Stars observation date unavailable · Downloads observation date unavailable
Exact implementation repository metric.
No exact package is documented.
Publisher activity observed September 13, 2026
Stale source snapshot - recheck needed
Source relationship: First-party MCP
Reviewed September 13, 2026
Evidence-backed setup
This profile has type-appropriate, source-backed setup rather than an MCP-server client connector configuration.
Capability
AI gateway/control plane that can act as an MCP client and server and apply access controls around MCP tools. Capabilities: Connect to upstream MCP servers; Expose MCP capabilities through Bifrost; Apply role/virtual-key/tool scoping and gateway controls; Use OAuth2 and gateway telemetry/audit features documented by Bifrost
Not measured yet
Estimated token footprint of the MCP tool schemas exposed to the agent.
Reviewed access
Review the exact access boundary before connecting this MCP to accounts, credentials, or sensitive data.
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github:maximhq is listed as First-party MCP in MCP100’s current evidence.
Current official resources:
Original product, capability, tool, and usage documentation from the MCP publisher. Installation sections appear under Install & Agents.
Bifrost is a high-performance AI gateway that unifies access to 23+ 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.
Bifrost supports enterprise-grade, private deployments for teams running production AI systems at scale. In addition to private networking, custom security controls, and governance, enterprise deployments unlock advanced capabilities including adaptive load balancing, clustering, guardrails, MCP gateway, and other features designed for enterprise-grade scale and reliability.
Bifrost uses a modular architecture for maximum flexibility:
bifrost/
├── npx/ # NPX script for easy installation
├── core/ # Core functionality and shared components
│ ├── providers/ # Provider-specific implementations (OpenAI, Anthropic, etc.)
│ ├── schemas/ # Interfaces and structs used throughout Bifrost
│ └── bifrost.go # Main Bifrost implementation
├── framework/ # Framework components for data persistence
│ ├── configstore/ # Configuration storage backends
│ ├── logstore/ # Request logging storage backends
│ └── vectorstore/ # Vector storages
├── transports/ # HTTP gateway and other interface layers
│ └── bifrost-http/ # HTTP transport implementation
├── ui/ # Web interface for HTTP gateway
├── plugins/ # Extensible plugin system
│ ├── governance/ # Budget management and access control
│ ├── jsonparser/ # JSON parsing and manipulation utilities
│ ├── logging/ # Request logging and analytics
│ ├── maxim/ # Maxim's observability integration
│ ├── mocker/ # Mock responses for testing and development
│ ├── semanticcache/ # Intelligent response caching
│ └── telemetry/ # Monitoring and observability
├── docs/ # Documentation and guides
└── tests/ # Comprehensive test suites
Bifrost adds virtually zero overhead to your AI requests. In sustained 5,000 RPS benchmarks, the gateway added only 11 µs of overhead per request.
| Metric | t3.medium | t3.xlarge | Improvement |
|---|---|---|---|
| Added latency (Bifrost overhead) | 59 µs | 11 µs | -81% |
| Success rate @ 5k RPS | 100% | 100% | No failed requests |
| Avg. queue wait time | 47 µs | 1.67 µs | -96% |
| Avg. request latency (incl. provider) | 2.12 s | 1.61 s | -24% |
Key Performance Highlights:
Complete Benchmarks: Performance Analysis
Complete Documentation: https://docs.getbifrost.ai
Join our Discord for community support and discussions.
Get help with:
We welcome contributions of all kinds! See our Contributing Guide for:
For development requirements and build instructions, see our Development Setup Guide.
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
Built with ❤️ by Maxim