Conecta LLMtoMD con tus herramientas de IA
Un solo servidor MCP, todos los asistentes. Usa tus documentos —convierte, busca y pregunta— dentro de Claude, ChatGPT, Cursor y tus propios agentes. Inicia sesión para las apps; una clave de API para el código.
La memoria de tu agente de código
Los agentes de programación olvidan. A medida que crece la conversación, la especificación se pierde del contexto y la IA empieza a adivinar. Mantén tus requisitos en LLMtoMD y tu agente podrá recuperarlos —el detalle exacto, cuando lo necesite— en lugar de perder el hilo.
Sube tu FRD
Arrastra tu documento de requisitos, especificación o notas de diseño: cualquier archivo o enlace.
Lo estructuramos
LLMtoMD lo convierte en Markdown limpio y consultable en tu biblioteca.
Tu agente recuerda
Cursor, Claude Code, VS Code o Antigravity lo consultan como contexto duradero.

Claude
Usa tus documentos dentro de Claude.ai, Claude Desktop y la Claude API.
Connector URL
https://mcp.llmtomd.com/mcpClaude.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."}],
)mic_YOUR_KEY con una clave de Configuración → Conecta tus herramientas de IA.Obtén una clave de API 
Cursor
Dale a la IA de Cursor tus documentos mientras programas.
Connector URL
https://mcp.llmtomd.com/mcp- 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
Dale a tu agente de programación de VS Code una base de conocimiento persistente: FRDs, especificaciones y documentos.
Connector URL
https://mcp.llmtomd.com/mcpGitHub Copilot (agent mode)
- 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
Deja que el agente de Google Antigravity consulte tus especificaciones y documentos de diseño mientras construye.
- 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" }
}
}
}mic_YOUR_KEY con una clave de Configuración → Conecta tus herramientas de IA.Obtén una clave de API 
ChatGPT
Añade LLMtoMD como conector en ChatGPT.
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
Llama a LLMtoMD desde la OpenAI Responses API o el Agents SDK.
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)mic_YOUR_KEY con una clave de Configuración → Conecta tus herramientas de IA.Obtén una clave de API 
LangChain
Carga las herramientas de LLMtoMD en un agente de LangChain / LangGraph.
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 agentmic_YOUR_KEY con una clave de Configuración → Conecta tus herramientas de IA.Obtén una clave de API 
LlamaIndex
Usa las herramientas de LLMtoMD en un agente de LlamaIndex.
- 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 agentmic_YOUR_KEY con una clave de Configuración → Conecta tus herramientas de IA.Obtén una clave de API Usa tus documentos en cada asistente
Convierte, busca y pregunta a través de tus archivos —dentro de Claude, ChatGPT, Cursor y tus propios agentes— con un solo servidor MCP.