MCP Integration
Custom Agents
Use Datagate MCP in your own agent code
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Use Datagate MCP in your own agent code
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
server_params = StdioServerParameters(
command="datagate-mcp",
env={"DATAGATE_API_KEY": "dg_live_..."}
)
async with stdio_client(server_params) as (read, write):
async with ClientSession(read, write) as session:
await session.initialize()
# Discover datasets
datasets = await session.call_tool("list_datasets", {})
print(datasets)
# Query
result = await session.call_tool("query", {
"dataset_ids": ["uuid-1"],
"text": "machine learning transformers",
"top_k": 5,
})
print(result)
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
const transport = new StdioClientTransport({
command: "npx",
args: ["-y", "@datagate/mcp"],
env: { DATAGATE_API_KEY: "dg_live_..." },
});
const client = new Client({ name: "my-agent", version: "1.0.0" });
await client.connect(transport);
// Discover tools
const tools = await client.listTools();
console.log(tools);
// List datasets
const datasets = await client.callTool({
name: "list_datasets",
arguments: {},
});
// Query
const results = await client.callTool({
name: "query",
arguments: {
dataset_ids: ["uuid-1"],
text: "machine learning transformers",
top_k: 5,
},
});
from datagate import DatagateClient
client = DatagateClient(api_key="dg_live_...")
datasets = await client.list_datasets() # returns list[Dataset]
response = await client.query(text="...", dataset_ids=["..."]) # returns QueryResponse
result = await session.call_tool("list_datasets", {}) # returns formatted text