How to Use the Doctolib MCP in LlamaIndex

Q: Can LlamaIndex index Doctolib practitioner lists?

Absolutely. You fetch the data using rechercherpraticiens and insert it into your LlamaIndex vector store. This makes practitioner data searchable across your entire index.

Q: Is Doctolib data updated in LlamaIndex?

You can re-run the disponibilites tool to refresh your index whenever needed. This ensures your search engine reflects the most current clinic slots.

Index your Doctolib medical history and availability directly into LlamaIndex for grounded, searchable insights.

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Connect Doctolib MCP to LlamaIndex

Create your Vinkius account to connect Doctolib to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Doctolib with LlamaIndex

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Index medical search results

Pipe `rechercher_praticiens` output into your vector store for persistent reference. LlamaIndex treats these practitioner profiles as indexable documents for future queries. This turns transient API results into a knowledge base. You can query your past searches to remember specific doctor details without re-running the API call.

Semantic availability tracking

Use `disponibilites` to feed slot data into your LlamaIndex knowledge graph. Your agent can then reason over historical availability trends. It makes your index smarter. You aren't just getting a raw list; you're building a searchable history of clinic capacity grounded in real data.

Contextual appointment management

Add `lister_rendez_vous` results to your index to keep track of past consultations. This allows your agent to answer questions about your medical history accurately. The system grounds its responses in your actual appointment records. It avoids guesswork by pulling directly from the `lister_rendez_vous` tool output.

Setup guide

Set up Doctolib MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Doctolib MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Doctolib tools.",
)
response = await agent.run("List recent Doctolib data")

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Common questions about Doctolib MCP in LlamaIndex

Absolutely. You fetch the data using `rechercher_praticiens` and insert it into your LlamaIndex vector store. This makes practitioner data searchable across your entire index.

Once indexed, you use your natural language query engine. The agent retrieves the relevant Doctolib details from your vector store to answer the request.

You can re-run the `disponibilites` tool to refresh your index whenever needed. This ensures your search engine reflects the most current clinic slots.

The server operates in a Vinkius-managed sandbox. It uses ephemeral sessions for every request, ensuring that your appointment details are never cached permanently.

Only the output of the tools you choose to index, such as practitioner profiles or appointment lists, is stored. Your raw account credentials are never touched.

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