MCP Builder
SkillAI & modelsPlan and build MCP servers with agent-friendly tools, schemas, error handling, and evaluation. Use when creating or refactoring MCP integrations.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the MCP Builder skill
What this skill tells your AI
The instructions your AI receives, as published by dkyazzentwatwa/chatgpt-skills in mcp-builder/SKILL.md and read by ahel’s review.
Build MCP servers around user workflows, not raw API endpoints.
Workflow
- Read the target API docs and identify the workflows an agent must complete end to end.
- Design a small tool surface with high-signal outputs, clear identifiers, and actionable errors.
- Implement shared infrastructure first: auth, request helpers, pagination, truncation, and formatting.
- Add tool schemas and docstrings that make correct usage obvious.
- Evaluate the server with realistic tasks before expanding scope.
Principles
- Prefer workflow tools over thin endpoint wrappers.
- Return concise, high-signal responses by default.
- Use human-readable identifiers whenever possible.
- Make error messages corrective: tell the agent what to try next.
- Design for limited context and large datasets.
Resources
references/mcp_best_practices.mdfor design principles that apply to every server.references/python_mcp_server.mdfor Python implementation patterns.references/node_mcp_server.mdfor TypeScript implementation patterns.scripts/connections.pyandscripts/evaluation.pyas repo-local helpers.
Deliverables
- A concrete tool inventory tied to user workflows.
- Strict input/output schemas.
- Evaluation prompts or scripts that confirm the server is usable by an agent.
Signals
- GitHub stars
- 100
- Forks
- 20
- Last commit
- Apr 2026
Advanced
- Catalog kind
- skill
- Gateway key
mcp-builder-dkyazzentwatwa- Source
- github.com/dkyazzentwatwa/chatgpt-skills