How to Use the EBI Proteins API MCP in Pydantic AI

Q: How do I initialize the EBI Proteins API MCP Server in Pydantic AI?

Use the unified MCPToolset class with your Vinkius HTTP endpoint URL. Pass this toolset to the Agent constructor using the toolsets argument to expose all 16 protein tools.

Q: Can Pydantic AI validate mass-spectrometry data from the EBI Proteins API?

Yes, when the agent calls getproteomics, the incoming peptide mappings and uniqueness flags are strictly typed. This ensures your agent only processes valid experimental mass-spec records.

Q: How does the agent search for specific features by type?

The agent calls searchfeaturesbytype using valid types like DOMAIN or TRANSMEM. The framework validates these arguments against the allowed string enum before sending the request to the server.

Expose the EBI Proteins API MCP Server to Pydantic AI for type-safe validation of UniProt sequence data.

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Create your Vinkius account to connect EBI Proteins API 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 Proteins API with Pydantic AI

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Validate UniProt data at runtime with Pydantic AI

`get_protein` fetches full sequence entries and maps them directly to strict Python types. If the API payload structure changes, your application fails immediately rather than processing corrupt sequence data. When your agent calls `get_protein_features` to look up active sites or domain boundaries, Pydantic AI validates every start/end position. This guarantees that your downstream analysis code never receives malformed coordinate integers.

Type-safe phenotype mapping using this MCP Server

`get_mutagenesis` retrieves experimental records containing wild-type residues, mutant residues, and functional descriptions. The framework enforces strict type checks on these amino acid positions before your agent reasons about them. By using this MCP Server, you prevent the agent from hallucinating sequence variants. Every single mutagenesis record is verified against the schema defined by the server's tools, keeping your clinical models accurate.

Query verified taxonomy nodes inside Pydantic AI

`get_taxonomy` returns scientific names, ranks, and lineage details validated against the NCBI taxonomy database. The agent uses this tool to resolve organism IDs, ensuring that only valid integers are passed to subsequent queries. When searching for specific proteomes, the agent calls `search_proteomes` to obtain reference statuses and protein counts. Pydantic AI parses this structured response, making it easy to pipe the validated data into your local databases.

Setup guide

Set up EBI Proteins API 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-proteins-api-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about EBI Proteins API MCP in Pydantic AI

Use the unified `MCPToolset` class with your Vinkius HTTP endpoint URL. Pass this toolset to the `Agent` constructor using the `toolsets` argument to expose all 16 protein tools.

The framework validates the payload against the tool's schema for `get_variation`. If there is a mismatch in wild-type or mutant residues, it raises a validation error immediately to prevent silent corruption.

Yes, when the agent calls `get_proteomics`, the incoming peptide mappings and uniqueness flags are strictly typed. This ensures your agent only processes valid experimental mass-spec records.

The agent calls `search_features_by_type` using valid types like DOMAIN or TRANSMEM. The framework validates these arguments against the allowed string enum before sending the request to the server.

All genetic variants and clinical significance data fetched via `search_variation` pass through an encrypted HTTPS connection. The Vinkius runtime executes in a zero-trust sandbox, meaning your search parameters are never logged or stored.

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