LLMtoMD
LLMtoMD is the memory layer for AI coding agents. It converts any document — PDF, DOCX, slides, spreadsheets, images, audio, even whole websites — into clean, structured Markdown, then exposes it over MCP so your agent can search your FRDs, specs, and API docs on demand instead of re-reading (or forgetting) them.
On a real 50-page spec, answering a question via retrieval used ~97% fewer tokens than holding the whole doc in context — and returned the exact, cited requirement.
Tools
list_documents/get_document— browse and read your librarysearch_documents— semantic search across your docsask_documents— RAG answer with citationsconvert_url— turn any web page into Markdownsave_note— write a decision/spec back into the knowledge baselist_collections— focus on one project
Connect (OAuth — no token to paste)
Cursor / VS Code: add the server URL https://mcp.llmtomd.com/mcp
Claude Code:
```bash
claude mcp add --transport http llmtomd https://mcp.llmtomd.com/mcp
```
Also works with Claude, Antigravity, and via API key for OpenAI / LangChain /
LlamaIndex. Full guides: https://llmtomd.com/integrations
Try it
- "List my LLMtoMD documents."
- "Using my documents, what are the authentication requirements?"
- "Convert https://example.com/article into Markdown and summarize it."
Free tier included (MCP on every plan) → https://llmtomd.com
Server Config
{
"mcpServers": {
"llmtomd": {
"url": "https://mcp.llmtomd.com/mcp"
}
}
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