gcontext-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@gcontext-mcplist all files in my workspace"
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.
gcontext-mcp
The local MCP connector for gcontext. Runs on your machine as a stdio MCP server, bridging your AI agent to your gcontext workspace in the cloud.
Structure (files, folders, types, secret names) lives in the cloud
Secret values and script execution stay local, on your machine
Install
Add to Claude Code:
claude mcp add-json gcontext-personal '{"type":"stdio","command":"uvx","args":["gcontext-mcp"],"env":{"GCONTEXT_TOKEN":"<your token>"}}'Or run directly:
uvx gcontext-mcpRelated MCP server: colab-mcp
Environment variables
Variable | Required | Description |
| yes | Your workspace token (from app.gcontext.ai) |
| no | API endpoint (default: |
Self-hosting
If you self-host the gcontext backend, point GCONTEXT_API_URL to your instance:
{"type":"stdio","command":"uvx","args":["gcontext-mcp"],"env":{"GCONTEXT_TOKEN":"<token>","GCONTEXT_API_URL":"http://localhost:5179"}}See self-hosting docs for backend setup.
What this connector does
The connector exposes MCP tools for reading, writing, searching, and managing files in your gcontext workspace. Secret values are stored locally (in ~/.gcontext/.env) and injected at script runtime without ever leaving your machine.
License
MIT
Tool Schema Changelog
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