Use PartFinder with Anthropic tool calling - PartFinder API

This page gives Claude the PartFinder API as tools. The Anthropic SDK’s tool runner (Python or TypeScript) calls call_tool / callTool for each tool call and sends the result back until Claude answers.

Install

pip install anthropic requests   # Python
npm install @anthropic-ai/sdk       # JavaScript
export ANTHROPIC_API_KEY="..."
export PARTFINDER_API_KEY="ak_..."

Save partfinder_tools.py or partfinder-tools.mjs next to your code. It builds the tools from the OpenAPI document and makes each call with the key from PARTFINDER_API_KEY.

Give the model the tools

from anthropic import Anthropic, beta_tool

from partfinder_tools import call_tool, operations

client = Anthropic()


def partfinder_tool(op):
    return beta_tool(
        lambda **args: call_tool(op["name"], args),
        name=op["name"],
        description=op["description"],
        input_schema=op["parameters"],
    )


runner = client.beta.messages.tool_runner(
    model="claude-opus-5-5",
    max_tokens=1024,
    tools=[partfinder_tool(op) for op in operations],
    messages=[{"role": "user", "content": "Is my PartFinder API key working?"}],
)
final_message = runner.until_done()

for block in final_message.content:
    if block.type == "text":
        print(block.text)

import Anthropic from "@anthropic-ai/sdk";
import { betaTool } from "@anthropic-ai/sdk/helpers/beta/json-schema";
import { operations, callTool } from "./partfinder-tools.mjs";

const client = new Anthropic();

const tools = operations.map((op) =>
  betaTool({
    name: op.name,
    description: op.description,
    inputSchema: op.parameters,
    run: (input) => callTool(op.name, input),
  }),
);

const finalMessage = await client.beta.messages.toolRunner({
  model: "claude-opus-5-5",
  max_tokens: 1024,
  tools,
  messages: [{ role: "user", content: "Is my PartFinder API key working?" }],
});

for (const block of finalMessage.content) {
  if (block.type === "text") console.log(block.text);
}

beta_tool (Python) and betaTool (JavaScript) take each operation’s JSON Schema as input_schema / inputSchema. The tool runner is in beta in the Anthropic SDK. Save it as agent.py or agent.mjs next to the tools file.

Jobs and refusals

searchParts, compareParts and analyzeBom start a job. call_tool (callTool) waits for the job and returns the finished result, so the model does not need to poll. A refused call returns the API’s JSON with its error code and summary, and the model reads it like any other result. See AI agent integration for the rest of the rules.