How to Use the EBI PDBe MCP in Pydantic AI

Q: Can I map UniProt sequences to EBI PDBe structures using Pydantic AI?

Yes, your Pydantic AI agent uses getuniprotmapping to obtain validated residue alignments. This ensures that sequence variants map to the exact 3D coordinates without index mismatch errors.

Q: How do I look up related structures?

Call getrelatedentries to find alternative conformations or mutant structures. This lets your Pydantic AI agent explore alternative shapes of your target protein safely.

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Connect EBI PDBe MCP to Pydantic AI

Create your Vinkius account to connect EBI PDBe to Pydantic AI 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 EBI PDBe with Pydantic AI

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Type-safe ligand extraction in Pydantic AI

The `get_ligand_monomers` tool extracts bound small molecules, chemical formulas, and weights into strictly validated structures. Your Pydantic AI agent guarantees that every returned EBI PDBe ligand field matches your expected schema before execution continues. This prevents silent failures when parsing complex chemical names. You can confidently pass these validated EBI PDBe outputs directly to your downstream virtual screening tools.

Validating structural quality with the MCP Server

The `get_quality_scores` tool returns resolution and validation metrics that your Pydantic AI model checks at the type level. The MCP Server ensures that your Pydantic AI agent rejects any structure that falls below your strict quality thresholds. This automated validation protects your molecular dynamics runs from bad inputs. It eliminates manual inspection of EBI PDBe electron density maps.

Precise secondary structure parsing

The `get_secondary_structure` tool counts helices and sheets per chain to map the protein's fold topology. Your Pydantic AI agent parses this topological data from EBI PDBe into type-safe Python objects for immediate analysis. By linking this with `get_residue_listing`, you get a complete, validated inventory of the protein's physical shape. This makes it easy to automate structural classification tasks without writing custom parsers.

Setup guide

Set up EBI PDBe MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "ebi-pdbe-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to EBI PDBe tools.",
)

result = await agent.run("List recent EBI PDBe transactions")
print(result.output)

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Common questions about EBI PDBe MCP in Pydantic AI

Use the MCPToolset class pointing to the Vinkius HTTP endpoint. Pass the toolset to your Pydantic AI Agent constructor to automatically enable type-safe EBI PDBe structural queries.

Pydantic AI raises a validation error immediately rather than letting your agent process corrupt EBI PDBe coordinate fields. This guarantees data integrity across your entire bioinformatics pipeline.

Yes, your Pydantic AI agent uses `get_uniprot_mapping` to obtain validated residue alignments. This ensures that sequence variants map to the exact 3D coordinates without index mismatch errors.

Call `get_related_entries` to find alternative conformations or mutant structures. This lets your Pydantic AI agent explore alternative shapes of your target protein safely.

Yes, all protein sequences, chemical structures, and target PDB IDs are processed in an isolated, ephemeral MCP sandbox. This data is destroyed immediately after your Pydantic AI agent completes its execution.

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