Add a DeepChat LLM provider through explicit reviewed source changes. Use when a developer asks Codex to add a provider, provider profile, upstream provider config, model catalog mapping, provider auth behavior, or a special provider adapter in this repository.
mcp-builder
mcp-builder is an open-source integrations skill for Claude Code and compatible agents, published by ThinkInAIXYZ. Its author describes it as: “Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or service…”. The project has 6.2k stars on GitHub and is available under the Apache-2.0 license. Add it to your setup with `git clone https://github.com/ThinkInAIXYZ/deepchat ~/.claude/skills/mcp-builder`.
What mcp-builder does
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.
Installation
Add mcp-builder to your agent with:
git clone https://github.com/ThinkInAIXYZ/deepchat ~/.claude/skills/mcp-builder Always review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.
What's inside
The SKILL.md for mcp-builder is organised into these sections:
- Overview
- 🚀 High-Level Workflow
- Phase 1: Deep Research and Planning
- Phase 2: Implementation
- Phase 3: Review and Test
- Phase 4: Create Evaluations
- 📚 Documentation Library
- Core MCP Documentation (Load First)
- SDK Documentation (Load During Phase 1/2)
- Language-Specific Implementation Guides (Load During Phase 2)
- Evaluation Guide (Load During Phase 4)
When to use it
Reach for mcp-builder when you want integrations help from your agent without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.
Strengths
- Clear Apache-2.0 license — safe to read and adapt
- Ships in ThinkInAIXYZ/deepchat, an established project with 6,228 GitHub stars
- Actively maintained (recent commits)
Topics
Frequently asked questions
- What does mcp-builder do?
- Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
- How do I install mcp-builder?
- Run git clone https://github.com/ThinkInAIXYZ/deepchat ~/.claude/skills/mcp-builder in your agent, then reload your skills. Review the source at https://github.com/ThinkInAIXYZ/deepchat before installing.
- Is mcp-builder free to use?
- Yes. mcp-builder is free and open source under the Apache-2.0 license, so you can read, run, and adapt it within that license's terms.
- Where does mcp-builder come from?
- mcp-builder ships inside ThinkInAIXYZ/deepchat, a repository that contains 25 catalogued skills in total. The repository's 6,228 GitHub stars apply to that whole collection, not to this skill on its own.
Related skills
More Integrations →Drive native desktop apps through DeepChat's built-in Computer Use tools. Use when the user asks to operate, inspect, automate, or perform a GUI task in a real desktop application.
Drive a native macOS app via the cua-driver MCP server or CLI — snapshot its AX tree, click/type/scroll by element_index, verify via re-snapshot. Use when the user asks you to operate, drive, automate, or perform a GUI task in a real macOS application on the host (e.g. "open a file in TextEdit", "navigate to /Applications in Finder", "click the Save button in Numbers").
Use the Feishu/Lark plugin MCP tools for Feishu documents, spreadsheets, knowledge content, and other matching workspace operations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.