
Mcp Builder
This is a comprehensive guide for building MCP servers that actually work well with LLMs. It walks you through research, implementation, testing, and creating evaluations with 10 complex questions to verify your server works. The opinionated take is useful: prioritize comprehensive API coverage over workflow shortcuts, use TypeScript with streamable HTTP for remote servers, and include structured outputs with clear error messages. The four phase structure keeps you from jumping straight to code before understanding the API you're wrapping. Most valuable are the specific patterns for tool design, the evaluation framework requiring realistic multi-step questions, and links to MCP protocol docs and SDK references you'll actually need while building.
- GitHub stars
- 6K
- last updated
- Jun 11, 2026
Install
$ npx -y skills add thinkinaixyz/deepchat --skill mcp-builder --agent claude-codeInstalls into .claude/skills of the current project.
Files
MCP Server Development Guide
Overview
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
Process
🚀 High-Level Workflow
Creating a high-quality MCP server involves four main phases:
Phase 1: Deep Research and Planning
1.1 Understand Modern MCP Design
API Coverage vs. Workflow Tools: Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage.
Tool Naming and Discoverability:
Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., github_create_issue, github_list_repos) and action-oriented naming.
Sponsors
Details
- Repository
- github.com/thinkinaixyz/deepchat
- Categories
- Documentation, Code Review & Quality, AI & Agent Building, Python
- License
- Apache-2.0
- First seen
- Jun 11, 2026