Chatgpt-skills mcp-builder

Plan and build MCP servers with agent-friendly tools, schemas, error handling, and evaluation. Use when creating or refactoring MCP integrations.

install
source · Clone the upstream repo
git clone https://github.com/dkyazzentwatwa/chatgpt-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/dkyazzentwatwa/chatgpt-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/mcp-builder" ~/.claude/skills/dkyazzentwatwa-chatgpt-skills-mcp-builder && rm -rf "$T"
manifest: mcp-builder/SKILL.md
source content

MCP Builder

Build MCP servers around user workflows, not raw API endpoints.

Workflow

  1. Read the target API docs and identify the workflows an agent must complete end to end.
  2. Design a small tool surface with high-signal outputs, clear identifiers, and actionable errors.
  3. Implement shared infrastructure first: auth, request helpers, pagination, truncation, and formatting.
  4. Add tool schemas and docstrings that make correct usage obvious.
  5. 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.md
    for design principles that apply to every server.
  • references/python_mcp_server.md
    for Python implementation patterns.
  • references/node_mcp_server.md
    for TypeScript implementation patterns.
  • scripts/connections.py
    and
    scripts/evaluation.py
    as 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.