import os
import anthropic

client = anthropic.Anthropic()

response = client.beta.messages.create(
    model="claude-opus-5",
    max_tokens=16000,
    betas=["mcp-client-2025-11-20"],
    thinking={"type": "adaptive"},
    mcp_servers=[
        {
            "type": "url",
            "url": "https://api.landrecords.us/mcp",
            "name": "landrecords",
            "authorization_token": os.environ["LR_TOKEN"],
        }
    ],
    tools=[{"type": "mcp_toolset", "mcp_server_name": "landrecords"}],
    system=(
        "You answer questions about U.S. land parcels using the landrecords tools. "
        "Call parcel_schema before writing your first filter. Use parcel_count for "
        "'how many' questions. Request only the columns you need."
    ),
    messages=[
        {
            "role": "user",
            "content": (
                "How many parcels in Alameda County, CA are single-family homes "
                "built after 1950 and assessed over $750k?"
            ),
        }
    ],
)

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

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

const response = await client.beta.messages.create({
  model: "claude-opus-5",
  max_tokens: 16000,
  betas: ["mcp-client-2025-11-20"],
  thinking: { type: "adaptive" },
  mcp_servers: [
    {
      type: "url",
      url: "https://api.landrecords.us/mcp",
      name: "landrecords",
      authorization_token: process.env.LR_TOKEN,
    },
  ],
  tools: [{ type: "mcp_toolset", mcp_server_name: "landrecords" }],
  messages: [
    {
      role: "user",
      content: "Who owns 123 Main St, Oakland, CA and what is it assessed at?",
    },
  ],
});

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

import asyncio
import json
import os

from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

MCP_URL = "https://api.landrecords.us/mcp"
HEADERS = {"Authorization": f"Bearer {os.environ['LR_TOKEN']}"}


async def main() -> None:
    async with streamablehttp_client(MCP_URL, headers=HEADERS) as (read, write, _):
        async with ClientSession(read, write) as session:
            await session.initialize()

            tools = await session.list_tools()
            print([t.name for t in tools.tools])

            result = await session.call_tool(
                "parcel_count",
                {
                    "where": [
                        {"column": "statefp", "op": "eq", "value": "06"},
                        {"column": "countyname", "op": "eq", "value": "Alameda"},
                        {"column": "yearbuilt", "op": "gt", "value": 1950},
                    ]
                },
            )
            # Every tool returns one text block containing JSON.
            payload = json.loads(result.content[0].text)
            print(payload["count"])


asyncio.run(main())

async def all_parcels(session, where, columns, page_size=1000):
    offset = 0
    while True:
        result = await session.call_tool(
            "parcel_query",
            {"where": where, "columns": columns, "limit": page_size, "offset": offset},
        )
        page = json.loads(result.content[0].text)
        rows = page["features"]
        for row in rows:
            yield row
        if len(rows) < page_size:
            return
        offset += page_size

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";

const transport = new StreamableHTTPClientTransport(
  new URL("https://api.landrecords.us/mcp"),
  {
    requestInit: {
      headers: { Authorization: `Bearer ${process.env.LR_TOKEN}` },
    },
  },
);

const client = new Client({ name: "parcel-script", version: "1.0.0" });
await client.connect(transport);

const result = await client.callTool({
  name: "parcel_by_address",
  arguments: { address: "123 Main St, Oakland, CA", distance_meters: 150 },
});

const payload = JSON.parse(result.content[0].text);
console.log(payload.geocode.label, payload.parcels.length);

await client.close();

You have access to the Land Records parcel tools (157M+ U.S. parcels, read-only).

- Call parcel_schema once before writing your first filter. Do not guess column names.
- For "how many" questions use parcel_count. Never page through rows to count them.
- Request only the columns you need via `columns`. The default returns ~50 per row.
- Filters are AND-only and unordered. There is no sorting — narrow with thresholds
  instead of asking for "the top N" over a large set.
- statefp is a two-digit FIPS string ('06', not 6); countyfp is three digits.
- Distances are meters. Coordinates are [longitude, latitude] in WGS84.
- Geometry is never returned; use centroidx/centroidy or the spatial tools.
- After parcel_by_address, state the geocode label you matched before reporting
  an owner or value, so the user can catch a wrong match.