Connect your agent to SingIt

from langchain_openai import ChatOpenAI
chat = ChatOpenAI(model="free/deepseek-v4.1-flash", api_key="unused", base_url="https://ask.singitai.app/v1", max_retries=0, max_tokens=60)
print("langchain-py:", repr(chat.invoke("Reply with the single word: pong").content)[:120])

import { ChatOpenAI } from "@langchain/openai";
const chat = new ChatOpenAI({ model: "free/deepseek-v4.1-flash", apiKey: "unused", maxRetries: 0, maxTokens: 60,
  configuration: { baseURL: "https://ask.singitai.app/v1" } });
const r = await chat.invoke("Reply with the single word: pong");
console.log("langchain-js:", JSON.stringify(r.content).slice(0,120));

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
async def main():
    c = MultiServerMCPClient({"singit": {"transport": "streamable_http", "url": "https://app.singitai.app/mcp"}})
    tools = await c.get_tools()
    print("langchain-py mcp tools:", len(tools), [t.name for t in tools][:3])
asyncio.run(main())

import { MultiServerMCPClient } from "@langchain/mcp-adapters";
const client = new MultiServerMCPClient({ mcpServers: { singit: { transport: "http", url: "https://app.singitai.app/mcp" } } });
const tools = await client.getTools();
console.log("langchain-js mcp tools:", tools.length, tools.slice(0,3).map(t=>t.name));
const t = tools.find(t=>t.name.endsWith("list_price_symbols"));
const out = await t.invoke({}); console.log(String(typeof out==="string"?out:JSON.stringify(out)).slice(0,150));
await client.close();

import { generateText } from "ai";
import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
const singit = createOpenAICompatible({ name: "singit", baseURL: "https://ask.singitai.app/v1", apiKey: "unused" });
const { text } = await generateText({ model: singit("free/deepseek-v4.1-flash"), prompt: "Reply with the single word: pong", maxOutputTokens: 60, maxRetries: 0 });
console.log("ai-sdk:", JSON.stringify(text).slice(0,120));

import { createMCPClient } from "@ai-sdk/mcp";
const c = await createMCPClient({ transport: { type: "http", url: "https://app.singitai.app/mcp" } });
const tools = await c.tools();
console.log("ai-sdk mcp tools:", Object.keys(tools).length, Object.keys(tools).slice(0,3));
await c.close();

from openai import AsyncOpenAI
from agents import Agent, Runner, OpenAIChatCompletionsModel, ModelSettings, set_tracing_disabled
set_tracing_disabled(True)
client = AsyncOpenAI(base_url="https://ask.singitai.app/v1", api_key="unused", max_retries=0)
agent = Agent(name="t", instructions="Answer in one word.", model=OpenAIChatCompletionsModel(model="free/deepseek-v4.1-flash", openai_client=client), model_settings=ModelSettings(max_tokens=60))
print("agents-py:", repr(Runner.run_sync(agent, "Reply with the single word: pong").final_output)[:120])

import OpenAI from "openai";
import { Agent, run, setDefaultOpenAIClient, setOpenAIAPI, setTracingDisabled } from "@openai/agents";
setTracingDisabled(true);
const client = new OpenAI({ baseURL: "https://ask.singitai.app/v1", apiKey: "unused", maxRetries: 0 });
setDefaultOpenAIClient(client); setOpenAIAPI("chat_completions");
const agent = new Agent({ name: "t", instructions: "Answer in one word.", model: "free/deepseek-v4.1-flash", modelSettings: { maxTokens: 60 } });
const r = await run(agent, "Reply with the single word: pong");
console.log("agents-js:", JSON.stringify(r.finalOutput).slice(0,120));

import asyncio
from agents.mcp import MCPServerStreamableHttp
async def main():
    async with MCPServerStreamableHttp(name="singit", params={"url": "https://app.singitai.app/mcp"}) as s:
        tools = await s.list_tools()
        print("agents-py mcp tools:", len(tools), [t.name for t in tools][:3])
asyncio.run(main())

import litellm
r = litellm.completion(model="openai/free/deepseek-v4.1-flash", api_base="https://ask.singitai.app/v1", api_key="unused",
    messages=[{"role":"user","content":"Reply with the single word: pong"}], max_tokens=60, num_retries=0)
print("litellm:", repr(r.choices[0].message.content)[:120])