APIs and frameworks

Model APIs and agent frameworks run without a person at a browser, so they connect with a Weir API key, sent as Authorization: Bearer <key>. Create one under API keys and keep it in WEIR_API_KEY.

Each example asks "What's my Weir usage?" A working connection calls get_usage, which is free.

Claude API

The Messages API connects to remote MCP servers itself, from Anthropic's cloud, so the URL has to be public. Pass the key as authorization_token:

import os

import anthropic

client = anthropic.Anthropic()

response = client.beta.messages.create(
    model="claude-opus-5-5",
    max_tokens=1024,
    betas=["mcp-client-2025-11-20"],
    mcp_servers=[
        {
            "type": "url",
            "url": "https://api.weirapp.io/mcp",
            "name": "weir",
            "authorization_token": os.environ["WEIR_API_KEY"],
        }
    ],
    tools=[{"type": "mcp_toolset", "mcp_server_name": "weir"}],
    messages=[{"role": "user", "content": "What's my Weir usage?"}],
)

Both halves are required: the server in mcp_servers, and an mcp_toolset that names it.

Claude MCP connector docs

OpenAI Responses API

OpenAI calls Weir from its own servers. Send the key in headers:

import os

from openai import OpenAI

client = OpenAI()

response = client.responses.create(
    model=os.environ["OPENAI_MODEL"],  # any model that supports remote MCP
    tools=[
        {
            "type": "mcp",
            "server_label": "weir",
            "server_url": "https://api.weirapp.io/mcp",
            "headers": {"Authorization": f"Bearer {os.environ['WEIR_API_KEY']}"},
            "require_approval": {"never": {"read_only": True}},
        }
    ],
    input="What's my Weir usage?",
)
print(response.output_text)

require_approval decides which calls stop and wait for your approval. The setting above lets tools marked read-only run straight away and asks before anything else. Leave it out and every call waits for approval.

The MCP tool is part of the Responses API. Chat Completions does not have it.

OpenAI MCP docs

OpenAI Agents SDK

Your process connects to Weir:

import asyncio
import os

from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp


async def main() -> None:
    async with MCPServerStreamableHttp(
        name="weir",
        params={
            "url": "https://api.weirapp.io/mcp",
            "headers": {"Authorization": f"Bearer {os.environ['WEIR_API_KEY']}"},
            "timeout": 30,
        },
        client_session_timeout_seconds=30,
        cache_tools_list=True,
    ) as weir:
        agent = Agent(name="analyst", mcp_servers=[weir])
        result = await Runner.run(agent, "What's my Weir usage?")
        print(result.final_output)


asyncio.run(main())

Raise the timeouts as shown. The SDK's default is five seconds, and a search or a comment tree can take longer. The JavaScript SDK's MCPServerStreamableHttp takes the same header under requestInit.headers.

Agents SDK MCP docs

LangChain

With langchain-mcp-adapters:

import asyncio
import os

from langchain_mcp_adapters.client import MultiServerMCPClient


async def main() -> None:
    client = MultiServerMCPClient(
        {
            "weir": {
                "transport": "streamable_http",
                "url": "https://api.weirapp.io/mcp",
                "headers": {"Authorization": f"Bearer {os.environ['WEIR_API_KEY']}"},
            }
        }
    )
    tools = await client.get_tools()
    print([tool.name for tool in tools])


asyncio.run(main())

LangChain prefixes the tool names with the server name. In JavaScript, @langchain/mcp-adapters takes the same url and headers.

LangChain MCP docs

Vercel AI SDK

import { createMCPClient } from "@ai-sdk/mcp";

const weir = await createMCPClient({
  transport: {
    type: "http",
    url: "https://api.weirapp.io/mcp",
    headers: { Authorization: `Bearer ${process.env.WEIR_API_KEY}` },
  },
});

const tools = await weir.tools();

Pass tools to generateText or streamText, and call weir.close() when you are done. createMCPClient comes from @ai-sdk/mcp, not from ai.

AI SDK MCP docs

n8n

Add an MCP Client Tool node to your AI agent and set:

Setting	Value
Endpoint	`https://api.weirapp.io/mcp`
Server Transport	HTTP Streamable
Authentication	Bearer Auth, with a credential holding your key
Tools to Include	All

Older workflows default the transport to SSE, which Weir does not serve. Switch it to HTTP Streamable. n8n's MCP OAuth2 credential also works, if you would rather sign in than store a key.

n8n MCP Client Tool docs