Introduction
Developers are increasingly blending multiple LLMs into their workflow. Connecting GitHub's MCP server with Claude Sonnet and GPT-5 through JuheAPI unlocks synchronized multi-LLM automation without leaving your repository environment.
GitHub MCP Overview
Core Capabilities
- Repository Management: Create, list, and validate repositories.
- Branch Lifecycle: Securely create, list, and delete branches.
- Issue Handling: Create, list, and filter by state.
- Pull Requests: Create, update, merge with multiple strategies.
- File Editing: Create/update with Base64 support.
- Releases: Draft and publish tagged releases.
Installation & Setup
Prerequisites:
- Node.js v16+
- GitHub personal access token
Steps:
- Clone repository:
git clone https://github.com/cyanheads/github-mcp-server.git
cd github-mcp-server
- Install dependencies:
npm install
- Environment variables:
GITHUB_TOKEN=your_github_personal_access_token
LOG_LEVEL=info
SERVER_NAME=github-mcp-server
- Build & start:
npm run build
node build/index.js
JuheAPI Multi-LLM Endpoints
What They Offer
JuheAPI provides simultaneous connections to multiple LLMs like Claude and GPT from a single API call.
Why They Fit MCP
MCP’s standardized interface means the GitHub context can be cleanly passed to specific LLM endpoints, returning structured actions.
Integrating Claude Sonnet via MCP
Configuring Endpoint
Set up an MCP tool targeting Claude Sonnet's JuheAPI route with repository context payloads.
Running Repository Queries
Example: Claude can generate detailed issue descriptions by analyzing file diffs retrieved via MCP.
Integrating GPT-5 via MCP
Jobs Best Suited
- Complex code reviews
- Designing branch strategies
Example: Pull Request Review
MCP fetches PR details and sends them to GPT-5 via JuheAPI to get architectural feedback.
Parallel Use: Claude + GPT-5
Coordinating Responses
Attach IDs to MCP calls to each LLM, then reconcile results in a merged GitHub comment.
Automated Workflows
Use Claude for summarization and GPT-5 for in-depth code analysis in one MCP-driven CI step.
Practical Walkthrough
Quick Start Example
- Configure MCP tools for Claude and GPT-5 endpoints via JuheAPI.
- Request: MCP fetches latest commits and sends:
{
"llm": "claude-sonnet",
"context": "recent commits"
}
- Claude summarizes changes; GPT-5 proposes refactor.
Debugging Tips
- Verify endpoint URLs in JuheAPI.
- Check MCP logs for payload formatting.
Benefits & Limitations
Benefits:
- Unified workflow in GitHub
- Multi-LLM insight without manual copy/paste
- Scalable automation
Limitations:
- Requires careful token management
- LLM quota limits
- Coordination overhead
Conclusion
By combining GitHub MCP’s powerful API integration with JuheAPI’s multi-LLM endpoints, developers can orchestrate Claude Sonnet and GPT-5 in parallel, automating repository management and code intelligence directly inside their dev flow.