How to Use the Ensembl MCP in LlamaIndex

Q: How do I load Ensembl tools into a LlamaIndex application?

Install llama-index-tools-mcp. Set up a BasicMCPClient pointing to the Vinkius URL, then pass it to McpToolSpec. Your agent can now call the endpoints.

Index live genomic structures from Ensembl into searchable LlamaIndex knowledge bases.

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Connect Ensembl MCP to LlamaIndex

Create your Vinkius account to connect Ensembl 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 Ensembl with LlamaIndex

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Claude

Perplexity

Indexing complex gene trees

LlamaIndex treats API outputs as documents. When you connect this MCP Server, your application doesn't just read data — it stores it. You can pull an entire evolutionary tree using `get_genetree` and embed it directly into your vector store. This means your query engine now understands genomic relationships. If a user asks about species homology, the system searches the indexed `get_homology` data instead of guessing. You get answers grounded in hard biological data.

RAG for clinical variant analysis

Building a RAG pipeline for clinical diagnostics requires exact variant consequences. You configure your LlamaIndex agent to hit `get_vep_hgvs` whenever it encounters a variant notation in your private medical documents. The agent fetches the live consequence data and synthesizes it with your internal PDFs. It merges the public `get_variation` facts with your proprietary research context. This creates a unified, highly accurate query response.

Cross-assembly coordinate mapping

Genomic coordinates shift between assembly versions, which ruins static databases. By giving LlamaIndex access to the `get_map` tool, your query engine can translate coordinates on the fly. If a user searches for a GRCh37 position, the agent checks `get_info_assembly`, maps it to GRCh38, and retrieves the correct overlapping features. The complexity of assembly conversion becomes completely invisible to the end user.

Setup guide

Set up Ensembl 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 Ensembl 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 Ensembl tools.",
)
response = await agent.run("List recent Ensembl data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Ensembl. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Ensembl MCP in LlamaIndex

Install `llama-index-tools-mcp`. Set up a `BasicMCPClient` pointing to the Vinkius URL, then pass it to `McpToolSpec`. Your agent can now call the endpoints.

That is exactly what it does best. You can route outputs from tools like `get_taxonomy_id` straight into your vector store. Future queries hit the index instead of the API.

Use the allowed tools filter when configuring the tool spec. If you only want your agent checking `get_sequence_id`, just pass that specific name.

Yes. Your agent can aggregate multiple identifiers from a document and hit `get_lookup_bulk` in a single pass. It embeds the entire batch response into the index.

The system processes raw cDNA coordinates and variant identifiers. Vinkius enforces a zero-trust architecture. Connections require a single endpoint token, and the network layer drops all state the millisecond the API returns the result.

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