This is your guide when you need to build an MCP server that lets LLMs talk to external APIs. It walks through the full workflow: researching the MCP spec and SDK docs, planning which API endpoints to expose as tools, implementing with proper schemas and error handling, and creating evaluations to test if LLMs can actually use what you built. Recommends TypeScript with streamable HTTP transport for remote servers, emphasizes comprehensive API coverage over custom workflows, and includes concrete advice on tool naming, pagination, and structured outputs. The evaluation section is especially useful since it forces you to prove your server works by creating ten complex, realistic questions that require multiple tool calls to answer.
- GitHub stars
- 298
- last updated
- Jun 11, 2026
Install
$ npx -y skills add syahiidkamil/software-engineer-ai-agent-atlas --skill mcp-builder --agent claude-codeInstalls into .claude/skills of the current project.
Files
This is your guide when you need to build an MCP server that lets LLMs talk to external APIs. It walks through the full workflow: researching the MCP spec and SDK docs, planning which API endpoints to expose as tools, implementing with proper schemas and error handling, and creating evaluations to test if LLMs can actually use what you built. Recommends TypeScript with streamable HTTP transport for remote servers, emphasizes comprehensive API coverage over custom workflows, and includes concrete advice on tool naming, pagination, and structured outputs. The evaluation section is especially useful since it forces you to prove your server works by creating ten complex, realistic questions that require multiple tool calls to answer.
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- Repository
- github.com/syahiidkamil/software-engineer-ai-agent-atlas
- Categories
- Documentation, Code Review & Quality, AI & Agent Building, Python
- First seen
- Jun 11, 2026
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