Which integrations are available for this server?

Provides Git integration with tools for cloning repositories, checking status, committing, pushing, and pulling changes. Provides compatibility with Google's Gemini Spark, allowing Spark to use the server's terminal tools such as command execution, file management, web requests, and system operations.

How do I use Spark Terminal MCP?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Spark Terminal MCP Check disk space and show me the results" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Spark Terminal MCP

A Gemini Spark-compatible MCP server with 30+ terminal tools — deployed on Render.

What this is

Gemini Spark requires custom Connected Apps to expose a full OAuth 2.1 discovery chain before it will call any tools:

Spec	Endpoint	Purpose
RFC 9728	`/.well-known/oauth-protected-resource`	Discover which auth server protects the tools
RFC 8414	`/.well-known/oauth-authorization-server`	Find token/registration/authorize endpoints
RFC 7591	`/api/oauth/register`	Dynamic Client Registration (auto-register)
RFC 7636	`/authorize` + `/api/oauth/token`	PKCE authorization-code flow

This server implements all four, plus the Streamable HTTP MCP transport that Spark uses.

Related MCP server: cloudflare-mcp-dcr-bridge

Tools (30+)

Group	Tools
Command Execution	`execute_command`, `run_python_code`, `stream_output`, `get_process_output`, `kill_process`
File Management	`read_file`, `write_file`, `delete_file`, `move_file`, `copy_file`, `list_directory`, `create_directory`
Web & Internet	`fetch_url`, `download_file_from_url`, `search_web`, `http_request`
Package & System	`install_package`, `get_system_info`, `list_processes`, `check_disk_space`, `view_logs`
Text Processing	`grep_file`, `find_files`, `replace_in_file`
Git	`git_clone`, `git_status`, `git_commit`, `git_push`, `git_pull`
Archive	`compress_files`, `extract_archive`
Network	`ping_host`, `check_port`, `get_ip_info`
System	`change_permissions`, `get_env_variable`, `set_env_variable`
Downloads	`get_download_url`, `clear_terminal`

Deploy to Render

Fork / clone this repo
Go to render.com → New → Web Service
Connect this repo, select Docker runtime
Set env var JWT_SIGNING_KEY to a random 64-char hex string
Deploy — get your https://spark-terminal-mcp.onrender.com URL

Connect to Gemini Spark

Go to gemini.google.com
Switch to Spark mode
Settings & help → Connected Apps → Add a custom app
Enter your Render URL: https://spark-terminal-mcp.onrender.com
Follow OAuth flow — click Connect

Local dev

pip install -r requirements.txt
AUTH_BYPASS=true python3 server.py
# Server on http://localhost:8080
# MCP endpoint: http://localhost:8080/mcp

Environment variables

Variable	Default	Description
`PORT`	`8080`	HTTP port
`AUTH_BYPASS`	`false`	Set `true` to skip auth (local dev only)
`JWT_SIGNING_KEY`	auto-generated	Secret for signing JWT tokens

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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