mcp-use

Provides opinionated TypeScript boilerplate and initialization patterns for building MCP servers compatible with the @modelcontextprotocol/sdk. Abstracts away protocol handshake, resource registration, and tool definition boilerplate through a fluent builder API that generates type-safe server instances with minimal configuration.

Implements MCP client initialization with support for multiple transport mechanisms (stdio, SSE, WebSocket) and automatic connection lifecycle management. Handles protocol negotiation, capability discovery, and graceful reconnection with exponential backoff, abstracting transport complexity behind a unified client interface.

Provides declarative validation of MCP requests and responses against schemas, with automatic error transformation and structured error responses. Validates tool parameters, resource requests, and response payloads before they reach handlers, and converts validation errors into MCP-compliant error responses with detailed error messages.

Provides a development server that automatically reloads MCP server code on file changes, integrates with Node.js debugger for breakpoint debugging, and includes a built-in MCP inspector UI for testing tools and resources without a client. Enables rapid iteration during development with instant feedback.

Provides a pluggable caching layer that automatically caches tool results and resource content based on configurable TTL and cache key strategies. Supports multiple cache backends (in-memory, Redis, Memcached) and includes cache invalidation patterns for handling stale data and cache busting.

Provides rate limiting and quota management for MCP tools and resources, supporting multiple strategies (token bucket, sliding window, fixed window) and quota scopes (per-user, per-IP, global). Integrates with the middleware pipeline to enforce limits transparently without modifying tool code.

Provides built-in OAuth 2.0 flow handling for MCP servers, enabling secure authentication and authorization without manual token management. Integrates with popular OAuth providers (Google, GitHub, etc.) and manages token refresh, expiration, and scope validation transparently within the MCP request/response cycle.

Implements sampling logic that dynamically filters available tools and resources based on request context, user permissions, and execution state. Uses a declarative sampling configuration to expose only relevant capabilities to the client, reducing token usage and improving agent decision-making by limiting the tool namespace.

Provides a notification system that allows MCP servers to push events and updates to connected clients in real-time using server-sent events (SSE) or WebSocket. Implements a publish-subscribe pattern where servers can emit notifications tied to specific resources or events, and clients can subscribe to receive updates without polling.

Provides built-in instrumentation for tracing MCP requests end-to-end, including tool execution time, resource access patterns, and error tracking. Integrates with standard observability backends (OpenTelemetry, Datadog, New Relic) and emits structured logs with request context, execution duration, and outcome metadata.

Provides first-class support for deploying MCP servers as ChatGPT Apps and Code Mode integrations, handling the specific authentication, capability declaration, and response formatting requirements of OpenAI's platforms. Automatically generates OpenAI-compatible action schemas and manages the ChatGPT-specific protocol handshake.

Provides TypeScript-first tool and resource definition APIs that enforce schema validation at compile-time and runtime. Uses JSON Schema internally with TypeScript generics to ensure tool parameters and resource content match declared types, preventing runtime type mismatches and enabling IDE autocomplete for tool parameters.

Enables composing multiple MCP servers into a single logical server using a middleware pipeline pattern. Allows intercepting and transforming requests/responses, implementing cross-cutting concerns (logging, rate limiting, caching) without modifying individual tool handlers, and delegating tool calls to downstream servers.

Supports streaming large resource content progressively to clients using chunked transfer encoding or server-sent events, avoiding memory exhaustion and enabling real-time content delivery. Implements backpressure handling to prevent overwhelming slow clients and supports resumable transfers for interrupted connections.