Integrations

Connect LLMtoMD to your AI tools

One MCP server, every assistant. Use your documents — convert, search, and ask — inside Claude, ChatGPT, Cursor, and your own agents. Sign in for apps; an API key for code.

Get started free API & MCP docs

For coding agents

Your code agent's memory

Coding agents forget. As the conversation grows, the spec slips out of context and the AI starts guessing. Keep your requirements in LLMtoMD and your agent can pull them back — the exact detail, on demand — instead of losing the thread.

Step 1

Upload your FRD

Drop in your requirements doc, spec, or design notes — any file or link.

Step 2

We structure it

LLMtoMD converts it to clean, searchable Markdown in your library.

Step 3

Your agent remembers

Cursor, Claude Code, VS Code, or Antigravity query it as durable context.

Claude

Use your documents inside Claude.ai, Claude Desktop, and the Claude API.

Sign-in

Connector URL

https://mcp.llmtomd.com/mcp

Claude.ai (web)

Open claude.ai → Settings → Connectors → Add custom connector (a paid plan is required).
Paste the Connector URL above, leave the OAuth fields blank, and click Connect.
Sign in to LLMtoMD and click Allow.

Claude Desktop

Settings → Developer → Edit config, add this to claude_desktop_config.json, then restart. The first run opens a browser to sign in:

{
  "mcpServers": {
    "llmtomd": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.llmtomd.com/mcp"]
    }
  }
}

Claude API

Pass LLMtoMD as a remote MCP server with an API key:

client.beta.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    mcp_servers=[{
        "type": "url",
        "name": "llmtomd",
        "url": "https://mcp.llmtomd.com/mcp",
        "authorization_token": "mic_YOUR_KEY",
    }],
    betas=["mcp-client-2025-11-20"],
    messages=[{"role": "user", "content": "List my LLMtoMD documents."}],
)

Replace mic_YOUR_KEY with a key from Settings → Connect your AI tools.Get an API key

Cursor

Give Cursor's AI your documents while you code.

Sign-in

Connector URL

https://mcp.llmtomd.com/mcp

Add to Cursor

Click Add to Cursor above and confirm the install — no file editing.
Cursor opens a browser to sign in to LLMtoMD the first time — no key needed.
Prefer to do it by hand? Create ~/.cursor/mcp.json (global) or .cursor/mcp.json (project) with the entry below instead.

{
  "mcpServers": {
    "llmtomd": { "url": "https://mcp.llmtomd.com/mcp" }
  }
}

VS Code

Give your VS Code coding agent a persistent knowledge base — FRDs, specs, and docs.

Sign-in

Connector URL

https://mcp.llmtomd.com/mcp

GitHub Copilot (agent mode)

Add to VS Code VS Code Insiders

Click Add to VS Code above, then Install in the prompt VS Code shows — no file editing.
The first run opens a browser to sign in to LLMtoMD (OAuth) — no key. After you approve, the tools appear in Copilot's agent mode.
Prefer to do it by hand? Command Palette → MCP: Open User Configuration and add the server below instead.

{
  "servers": {
    "llmtomd": { "type": "http", "url": "https://mcp.llmtomd.com/mcp" }
  }
}

Claude Code (in VS Code or the terminal)

Claude Code has no one-click link (it keeps its own config). Run this once, then /mcp to finish the sign-in:

claude mcp add --transport http llmtomd https://mcp.llmtomd.com/mcp

Claude Code — share with a repo (.mcp.json)

Commit a .mcp.json at the repo root so everyone who opens it gets LLMtoMD (Claude Code prompts to approve on first use):

{
  "mcpServers": {
    "llmtomd": { "type": "http", "url": "https://mcp.llmtomd.com/mcp" }
  }
}

Antigravity

Let Google Antigravity's agent reference your specs and design docs while it builds.

API key

Antigravity Settings → Customizations → Open MCP Config (or edit ~/.gemini/config/mcp_config.json). Note: Antigravity uses serverUrl, not url.
Generate an API key below and paste it into the Authorization header (recommended — Antigravity's sign-in for custom servers is new and can hang mid-OAuth; the key always works).
Save and restart Antigravity; the LLMtoMD tools appear under Manage MCP servers.

{
  "mcpServers": {
    "llmtomd": {
      "serverUrl": "https://mcp.llmtomd.com/mcp",
      "headers": { "Authorization": "Bearer mic_YOUR_KEY" }
    }
  }
}

Replace mic_YOUR_KEY with a key from Settings → Connect your AI tools.Get an API key

ChatGPT

Add LLMtoMD as a connector in ChatGPT.

Sign-in

Connector URL

https://mcp.llmtomd.com/mcp

Enable Developer Mode: ChatGPT → Settings → Connectors (Apps) → Advanced → Developer mode (Plus/Pro/Team/Enterprise, beta).
In a chat, open the + (or Settings → Connectors) → Add a custom connector with the Connector URL above.
Sign in to LLMtoMD and click Allow.

OpenAI API

Call LLMtoMD from the OpenAI Responses API or Agents SDK.

API key

Responses API

from openai import OpenAI

client = OpenAI()
resp = client.responses.create(
    model="gpt-5",
    tools=[{
        "type": "mcp",
        "server_label": "llmtomd",
        "server_url": "https://mcp.llmtomd.com/mcp",
        "authorization": "mic_YOUR_KEY",
        "require_approval": "never",
    }],
    input="List my LLMtoMD documents.",
)
print(resp.output_text)

Agents SDK

from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async with MCPServerStreamableHttp(
    name="LLMtoMD",
    params={
        "url": "https://mcp.llmtomd.com/mcp",
        "headers": {"Authorization": "Bearer mic_YOUR_KEY"},
    },
) as server:
    agent = Agent(name="Assistant", instructions="Use the LLMtoMD tools.", mcp_servers=[server])
    print((await Runner.run(agent, "List my LLMtoMD documents.")).final_output)

Replace mic_YOUR_KEY with a key from Settings → Connect your AI tools.Get an API key

LangChain

Load LLMtoMD's tools into a LangChain / LangGraph agent.

API key

LangSmith / Fleet (no code)

In LangSmith → Settings → MCP servers → Add server → Add custom MCP.
Name it "llmtomd" and set the URL to https://mcp.llmtomd.com/mcp.
Under Authentication keep Static Headers, click Add header, and set Key to Authorization and Value to the line below. (Or choose OAuth 2.1 (Auto) to sign in instead of pasting a key.)
Save server — the LLMtoMD tools now show under Tools and are available to your Fleet agents.

Authorization: Bearer mic_YOUR_KEY

Python (langchain-mcp-adapters)

Install the adapter: pip install langchain-mcp-adapters

from langchain_mcp_adapters.client import MultiServerMCPClient

client = MultiServerMCPClient({
    "llmtomd": {
        "transport": "streamable_http",
        "url": "https://mcp.llmtomd.com/mcp",
        "headers": {"Authorization": "Bearer mic_YOUR_KEY"},
    }
})
tools = await client.get_tools()  # pass these into your agent

Replace mic_YOUR_KEY with a key from Settings → Connect your AI tools.Get an API key

LlamaIndex

Use LLMtoMD's tools in a LlamaIndex agent.

API key

Install the tools package: pip install llama-index-tools-mcp

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

client = BasicMCPClient("https://mcp.llmtomd.com/mcp", headers={"Authorization": "Bearer mic_YOUR_KEY"})
tools = McpToolSpec(client=client).to_tool_list()  # pass these into your agent

Replace mic_YOUR_KEY with a key from Settings → Connect your AI tools.Get an API key

Use your documents in every assistant

Convert, search, and ask across your files — inside Claude, ChatGPT, Cursor, and your own agents, over one MCP server.

Convert your first document free See pricing