A side-by-side look at the 6DuckLearn MCP and Kastell MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose 6DuckLearn MCP for knowledge & memory work; choose Kastell for security as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose 6DuckLearn MCP when
You need dedicated capabilities in the Knowledge & Memory domain.
No tool names declared yet. Check the project README from the listing page.
Kastell 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.
6DuckLearn MCP
No confirmed install command for 6DuckLearn MCP yet — follow the setup steps linked from its listing page rather than a guessed package name.
6DuckLearn MCP is categorized under Knowledge & Memory and uses an install path we have not confirmed yet. Kastell belongs to Security and uses a local stdio subprocess. Pick 6DuckLearn MCP for knowledge & memory work and Kastell for security.
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. 6DuckLearn MCP has no confirmed install command yet — follow its own setup instructions.
6DuckLearn MCP has no declared pricing — check the project's own site. Kastell is listed as free. Auth: no auth required. 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 6ducklearn-mcp and kastelldev-kastell as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, 6DuckLearn MCP has a quality signal of 33/100 (Emerging) with 0 views, 0 installs and 1 GitHub stars. Kastell has 61/100 (Good) with 4 views, 0 installs and 60 GitHub stars.