-
securityF
license-
qualityEnables AI assistants to enhance their responses with relevant documentation through a semantic vector search, offering tools for managing and processing documentation efficiently.
Last updated -
18
41
uptodoc
A lightweight MCP (Model Context Protocol) server for IDE-integrated AI agents (e.g., GitHub Copilot, Roocode, Cursor, Windsurf).
Overview
uptodoc provides a local server implementing the Model Context Protocol
(MCP).
It allows AI assistants integrated into IDEs like VSCode to query a custom
documentation database, offering more relevant and up-to-date information about
libraries and frameworks.
Once configured in your IDE, the assistant will automatically communicate with uptodoc to enhance coding suggestions.
Typical use cases:
- Fetching more recent or project-specific documentation
- Improving AI suggestions in coding assistants
- Extending Copilot, Roocode, Cursor, or Windsurf with custom knowledge
Requirements
- Node.js version 22 or higher
- VSCode version 1.99.3 or higher (or any compatible MCP client)
Make sure these tools are installed and up to date before using uptodoc.
Installation
You don't need to install uptodoc globally.
It is automatically launched by your IDE when configured correctly.
Make sure npx is available on your system (comes with Node.js).
Note: The package must be available on npm under the name
@jlgformation/uptodoc.
IDE Configuration
To use uptodoc in VSCode, add the following to your settings (e.g.,
.vscode/settings.json) :
Put the Github Copilot AI Assistant in agent mode. Then start the MCP server
on vscode.
You should be able to talk to the AI assistant. Do not hesitate to add in your
prompt the magical formula: use uptodoc.
Example:
As you can see above, the endpoint for the documentation can be configured. By default it is:
And there are some stupid docs: https://github.com/jlg-formation/uptodoc/tree/master/docs
References
Author
Jean-Louis GUENEGO jlguenego@gmail.com
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Enables AI assistants in IDEs to query custom documentation databases for more relevant and up-to-date information about libraries and frameworks. Improves coding suggestions by providing project-specific documentation through a configurable endpoint.
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