A side-by-side look at the Campus Cli and Learn with Agents MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Campus Cli for education work as a local process; choose Learn with Agents for education. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Campus Cli when
You need dedicated capabilities in the Education domain.
No tool names declared yet. Check the project README from the listing page.
Learn with Agents tools
No tool names declared yet. Check the project README from the listing page.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
No confirmed install command for Learn with Agents yet — follow the setup steps linked from its listing page rather than a guessed package name.
Frequently asked questions
Campus Cli is categorized under Education and uses a local stdio subprocess. Learn with Agents belongs to Education and uses an install path we have not confirmed yet. Pick Campus Cli for education work and Learn with Agents for education.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client. Learn with Agents has no confirmed install command yet — follow its own setup instructions.
Campus Cli has no declared pricing — check the project's own site. Learn with Agents has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add campus-cli and learn-with-agents as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Campus Cli has a quality signal of 47/100 (Fair) with 0 views, 0 installs and 11 GitHub stars. Learn with Agents has 37/100 (Fair) with 0 views, 0 installs and 0 GitHub stars.