AI editor setup
Give your AI coding assistant knowledge of the OneSource documentation so it can answer questions and generate accurate calls without you copy-pasting from these pages.
@one-source/mcp includes the documentation tools, so it covers this guide on its own. The options below are for wiring in the docs without the chain tools.
There are three ways to do it, in rough order of preference.
1. Recommended: the OneSource docs MCP
@one-source/docs-mcp gives your assistant structured tools, search docs, list endpoints, look up parameters, pricing, and auth, which retrieve far more precisely than plain text search. Two ways to run it:
- Hosted, zero install: point any HTTP-capable MCP client at
https://docs.onesource.io/api/mcp. - Local:
npx -y @one-source/docs-mcp(Node).
Per-editor configuration (Claude Code, Claude Desktop, Cursor, Windsurf, VS Code) lives on the Docs MCP page; start there.
2. Already using mcpdoc?
If you've standardized on LangChain's mcpdoc across your documentation sources, add OneSource as one more entry rather than running a second kind of server. It serves keyword search over llms.txt (no structured tools) and needs Python's uv: curl -LsSf https://astral.sh/uv/install.sh | sh.
Claude Code:
claude mcp add-json onesource-docs '{"type":"stdio","command":"uvx","args":["--from","mcpdoc","mcpdoc","--urls","OneSourceDocs:https://docs.onesource.io/llms.txt","--follow-redirects"]}'
Cursor / Windsurf / Claude Desktop: add to your editor's MCP config file (VS Code uses a servers key instead of mcpServers):
{
"mcpServers": {
"onesource-docs": {
"command": "uvx",
"args": ["--from", "mcpdoc", "mcpdoc", "--urls", "OneSourceDocs:https://docs.onesource.io/llms.txt", "--follow-redirects"]
}
}
}
3. No MCP support: use the raw files
If your tool can't speak MCP, point it at (or paste in) the doc bundles directly:
- llms.txt: index of every page (lightweight, for discovery).
- llms-full.txt: the full docs concatenated into one file (for context-window ingestion).