Self-Hosted GitHub Bot Runs Claude Code with 40+ Webhook Triggers and MCP Tools

A new open-source project, Claude Code GitHub Agent, provides a self-hosted bot that gives Claude Code 40+ GitHub webhook triggers and MCP (Model Context Protocol) tools. It runs the Claude Agent SDK with the full Claude Code feature set in isolated worktrees.
Key Features
- 4 Built-in MCP Servers: GitHub, GitHub Actions, Memory, and Codebase Tools.
- YAML-Based Triggers: Configure workflows in a
workflowsblock. Example:
workflows:
review-pr:
triggers:
events:
- event: pull_request.opened
- event: pull_request.labeled
filters:
label.name: ["review", "pr-review", "review-pr"]
commands:
- /review
- /pr-review
- /review-pr
prompt:
template: "/pr-review-toolkit:review-pr {repo} {issue_number}"This triggers the 'pr-review-toolkit' on opened PRs, on labeled PRs matching those names, and on slash commands in comments.
- Built-in Workflows: PR review, CI auto-fix, issue triage.
- Plugins: Add specialized agents.
- Persistent Memory: Cross-session persistence.
- Flexible Backend: Supports any Anthropic-compatible API (Ollama, Vertex, Z.AI).
Status
The project is still in beta (some internals to clean up) but fully usable. Feedback and contributions are welcome.
Who it's for: Developers who want to automate GitHub workflows using Claude Code with custom triggers and MCP tools, fully self-hosted.
📖 Read the full source: r/ClaudeAI
👀 See Also

InsForge: A Backend Semantic Layer for Claude Code Agents
InsForge exposes six backend primitives—authentication, Postgres database, S3-compatible storage, edge/serverless functions, model gateway, and site deployment—as structured components that Claude Code agents can inspect and configure via MCP instead of guessing API integrations.

PhAIL Benchmark Tests VLA Models on Real Warehouse Robot Tasks
PhAIL is a real-robot benchmark that tests four vision-language-action models on bin-to-bin order picking using a Franka FR3 robot. The best model achieved 64 units per hour, compared to 330 UPH for human teleoperation and 1,300+ UPH for human manual work.

Brunnfeld Agentic World: Multi-Agent Medieval Economy Simulation Without Behavioral Prompts
A TypeScript simulation where 20 LLM agents autonomously trade in a medieval village economy with no behavioral instructions, goals, or trading strategies. Agents receive ~200 token perceptions each tick and interact through a deterministic engine handling physics, recipes, and market mechanics.

Xiaozhen: A Claude Code skill that digs three layers into root causes
Xiaozhen (小真) is a Claude Code skill that uses three mechanics—The Gift, Three Layers Deep, and The Prediction—to help users uncover what's actually bothering them rather than giving direct advice. It's installed with a one-line curl command and activated by typing /小真 in Claude Code.