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Amirbiron MCP Server

Provides an extended MCP server for managing code snippets, render deployments, and Claude integrations.

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "amirbiron-mcp-server": {
      "url": "https://YOUR-APP.onrender.com/mcp",
      "headers": {
        "MONGO_URI": "mongodb://user:pass@host:port/db",
        "GITHUB_REPO": "owner/repo",
        "GITHUB_TOKEN": "YOUR_GITHUB_TOKEN",
        "RENDER_API_KEY": "YOUR_RENDER_API_KEY",
        "RENDER_SERVICE_ID": "service-id"
      }
    }
  }
}

You are deploying an extended MCP server designed to manage code snippets, render deployments, and integrate with Claude. It offers built‑in tools to organize, analyze, deploy, and monitor code in a centralized environment, streamlining development workflows and collaboration.

How to use

You will interact with the MCP server through a client that speaks the MCP protocol. Use the provided tools to manage code snippets, analyze code, render deployments, and collaborate with Claude. Typical workflows include creating and updating snippets, analyzing them for patterns, triggering new deploys, viewing service status, and opening issues on GitHub when problems are found.

How to install

Prerequisites: ensure you have Python installed on your system.

1) Clone the repository and navigate into the project folder.

2) Create a Python virtual environment and activate it.

3) Install dependencies from the requirements file.

4) Copy the example environment file and edit it to include your configuration values.

5) Start the MCP server.

Additional sections

Configuration includes environment variables for deployment and integration. The server can run locally for testing or deploy to a hosting platform. Security is enforced by stateless operation and environment‑variable masking for sensitive values. Deploy or restart actions require explicit checks before proceeding, and no secrets are stored in code.

Security notes

The server operates in stateless mode to support horizontal scaling. Sensitive values are masked in environment listings. Deploy and restart actions require a verification step to proceed. No secrets are stored in code; everything is handled via environment variables.

Available tools

list_snippets

Return a filtered list of code snippets by language, tag, or search term.

get_snippet

Retrieve a single snippet by its identifier.

create_snippet

Create a new code snippet with metadata and content.

update_snippet

Update an existing snippet with new content or metadata.

delete_snippet

Delete a snippet from the repository.

search_by_code

Perform a regex search inside code across snippets.

get_stats

Return statistics about the snippet repository.

analyze_snippet

Analyze a snippet for metrics, problematic patterns, and recommended improvements.

bulk_tag_snippets

Update tags on multiple snippets in a single operation.

render_service_status

Check the current status of the render service.

render_list_deploys

List recent deployments from the render service.

render_trigger_deploy

Trigger a new deployment for a service.

render_restart_service

Restart the render service to recover from issues.

render_get_env_vars

Show environment variables with sensitive values masked.

github_create_issue

Create a new GitHub issue (supports Markdown).

github_list_issues

List issues with optional filtering.

code_review

Provide a professional code review of the supplied snippet.

debug_help

Analyze an error, identify root causes, and suggest fixes.

create_github_issue_prompt

Template for creating GitHub issues (bug/enhancement).

deploy_check

Security checks to perform before initiating a deploy.

summarize_logs

Analyze logs to identify errors and anomalies.

optimize_snippet

Provide optimization suggestions for a snippet.