How does result streaming work in this skill?

It provides a structured way to yield partial results and progress updates using AsyncIterators, allowing the AI to provide feedback to the user before a long task is fully complete.

What anti-patterns does this skill address?

It helps developers avoid common pitfalls such as blocking the async event loop, failing to implement timeouts on external calls, and creating race conditions in shared state.

What are MCP Advanced Tool Patterns?

They are standardized implementation strategies for building high-performance Model Context Protocol tools, focusing on streaming, concurrency, and reliability within the Claude Code ecosystem.

Can I use this for multi-step workflows?

Absolutely. The skill includes an orchestration pattern that allows you to define tool dependencies and pass data between sequential tool calls automatically.

Does this skill support Python 3.13 features?

Yes, it includes patterns specifically designed for Python 3.13, such as using TaskGroups for concurrent execution instead of older methods like asyncio.gather.

MCP Advanced Tool Patterns

Name: MCP Advanced Tool Patterns
Author: Agentient

byAgentient

0•

API Development

Implements sophisticated Model Context Protocol integration patterns including result streaming, tool orchestration, and asynchronous execution workflows.

This skill provides a comprehensive library of design patterns for the Model Context Protocol (MCP), enabling developers to build more robust and responsive AI tools. It covers critical implementation details such as incremental result streaming for long-running tasks, multi-tool orchestration with dependency resolution, and advanced concurrency management using modern Python async features. By standardizing progress reporting, cancellation logic, and stateful session management, it ensures that Claude can interact with complex backend systems reliably and efficiently while avoiding common pitfalls like blocking operations or race conditions.

Key Features

01Advanced concurrency control using Python 3.13 TaskGroups

020 GitHub stars

03Incremental result streaming with real-time progress reporting

04Built-in cancellation support and timeout handling for long-running operations

05Multi-tool orchestration for complex, dependent workflows

06Stateful session management and optimized batch processing patterns

Use Cases

01Implementing high-performance data processing tools with exponential backoff and retries

02Building a code search tool that streams matches to the user as they are found

03Coordinating a sequence of API calls where later steps depend on earlier results

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add agentient/vibekit mcp-advanced-tool-patterns

For use in Claude.ai and ChatGPT

Key Features

01Advanced concurrency control using Python 3.13 TaskGroups

020 GitHub stars

03Incremental result streaming with real-time progress reporting

04Built-in cancellation support and timeout handling for long-running operations

05Multi-tool orchestration for complex, dependent workflows

06Stateful session management and optimized batch processing patterns

Use Cases

01Implementing high-performance data processing tools with exponential backoff and retries

02Building a code search tool that streams matches to the user as they are found

03Coordinating a sequence of API calls where later steps depend on earlier results