Does Gateway support complex service call chains?

Yes, Gateway fully supports multi-tool invocation chains within the MCP protocol. It offers flexible price aggregation strategies such as maximal, additive, and mean to manage pricing across these complex call sequences.

What is Gateway and its primary function?

Gateway is a service governance framework designed for MCP (Model Context Protocol) tool calls. Its primary function is to dynamically adjust the 'price' of service calls based on real-time server load and control client access using token budgets to prevent system overload.

How does Gateway prevent service overload?

Gateway prevents overload through three core mechanisms: dynamic pricing (adapting call costs to server load), server-side load shedding (rejecting requests if client tokens are below the dynamic price), and client-side rate limiting (proactively blocking requests when tokens are insufficient).

What metrics does Gateway use for dynamic pricing and overload detection?

Gateway uses advanced overload detection mechanisms including Go runtime scheduler's queuing delay histograms, throughput counters, and business latency to accurately assess real-time server load and adjust prices accordingly.

Is Gateway specific to a particular protocol?

Yes, Gateway is specifically integrated with and fully supports the JSON-RPC 2.0 based MCP protocol, handling standard methods like `initialize`, `tools/list`, `tools/call`, and governance metadata.

Gateway: Dynamic Pricing & Load Control for MCP Services

The mcp_gateway is a robust service governance engine designed for Model Context Protocol (MCP) tool invocation scenarios. It implements a dynamic pricing model where each MCP tool call has a fluctuating 'price' determined by server load, such as queuing delay or throughput. Clients carry a 'token' budget with their requests, and the server actively rejects requests (load shedding) when the client's tokens are insufficient to meet the current price, thus protecting the service from overload. Simultaneously, the framework empowers clients to implement rate limiting, preventing requests from being sent when their token budget is inadequate, ensuring a resilient and adaptive system for managing resource consumption.

Características Principales

01Comprehensive Overload Detection: Utilizes advanced mechanisms like Go runtime scheduler's queuing delay histograms and throughput counters to accurately identify congestion.

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03Server-side Load Shedding: Implements admission control, rejecting requests when client tokens fall below the dynamic price to prevent service overload.

04MCP Protocol Integration: Fully supports the JSON-RPC 2.0 based MCP protocol, including `initialize`, `tools/list`, `tools/call`, and governance metadata.

05Dynamic Pricing: Automatically adjusts tool call prices based on real-time server load metrics (e.g., queuing delay, throughput, business latency).

06Client-side Rate Limiting: Enables clients to proactively block requests when their token budget is insufficient, reducing unnecessary load on services.

07Flexible Price Aggregation: Supports multiple strategies for aggregating prices (maximal, additive, mean) across multi-tool invocation chains.

Casos de Uso

01Protecting backend services from overload during high-volume MCP tool invocations within AI agent ecosystems.

02Ensuring service stability and responsiveness by dynamically adapting to fluctuating request loads and preventing cascading failures.

03Implementing fair resource allocation and cost management for parallel tool calls initiated by AI agents or other clients.