One MCP endpoint. 500+ tools. Works with every major AI framework.
https://apibase.pro/mcp
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"apibase": {
"url": "https://apibase.pro/mcp",
"transport": "streamable-http"
}
}
}
No API key needed — auto-registration on first call. Optional: add "headers": {"Authorization": "Bearer ak_live_..."}
Add to .cursor/mcp.json in your project root:
{
"mcpServers": {
"apibase": {
"url": "https://apibase.pro/mcp",
"transport": "streamable-http"
}
}
}
Or install via Cursor Settings → MCP → Add Server → URL: https://apibase.pro/mcp
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"apibase": {
"serverUrl": "https://apibase.pro/mcp",
"transport": "streamable-http"
}
}
}
Or: Windsurf → Cascade → MCP Tools → Add Server
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHTTP, MCPServerManager
# MCPServerManager handles lifecycle of all MCP connections
async with MCPServerManager(
servers=[
MCPServerStreamableHTTP(
url="https://apibase.pro/mcp",
headers={"Authorization": "Bearer ak_live_..."}
)
]
) as manager:
agent = Agent(
name="my-agent",
instructions="You have access to 500+ real-world API tools.",
mcp_servers=manager.servers
)
result = await Runner.run(agent, "Search flights from NYC to London")
print(result.final_output)
MCPServerManager is the recommended way to manage multiple MCP connections. See official docs.
import { MCPServerStreamableHTTP } from "@openai/agents/mcp";
const server = new MCPServerStreamableHTTP({
url: "https://apibase.pro/mcp",
headers: { Authorization: "Bearer ak_live_..." }
});
await server.connect();
from langchain_mcp_adapters.client import MultiServerMCPClient
async with MultiServerMCPClient({
"apibase": {
"url": "https://apibase.pro/mcp",
"transport": "streamable_http",
"headers": {"Authorization": "Bearer ak_live_..."}
}
}) as client:
tools = client.get_tools()
# Use with any LangChain agent
from langgraph.prebuilt import create_react_agent
agent = create_react_agent(model, tools)
Install: pip install langchain-mcp-adapters
from google.adk.tools.mcp_tool import McpToolset, StreamableHTTPConnectionParams
toolset = McpToolset(
connection_params=StreamableHTTPConnectionParams(
url="https://apibase.pro/mcp",
headers={"Authorization": "Bearer ak_live_..."}
)
)
tools, exit_stack = await toolset.create_tools()
# tools is a list of BaseTool — use with any ADK agent
Install: pip install google-adk
from crewai import Agent, Task, Crew
agent = Agent(
role="Research Assistant",
goal="Find real-time data using 500+ API tools",
backstory="You have access to APIbase MCP server with tools for flights, weather, stocks, jobs, and more.",
mcp_servers=["https://apibase.pro/mcp"],
verbose=True
)
CrewAI auto-discovers tools via MCP. No manual tool registration needed.
In Copilot Studio → Actions → Add MCP Server:
Server URL: https://apibase.pro/mcp
Transport: Streamable HTTP
Authentication: Bearer token (optional — auto-registration supported)
Requires Microsoft 365 Copilot license. MCP support is GA as of 2026.
Sunpeak is an open-source framework for building interactive MCP Apps that run inside ChatGPT and Claude. Connect APIbase as a backend to give your app access to 500 real-world API tools — flights, finance, weather, government data, museums, and more.
import { createApp } from "sunpeak";
const app = createApp({
mcpServers: [
{
name: "apibase",
url: "https://apibase.pro/mcp",
transport: "streamable-http"
}
]
});
// Your app now has access to 500 tools via MCP
// Use discover_tools prompt to find relevant tools by task
await app.run();
Install: pnpm add -g sunpeak · Docs: sunpeak.ai · No API key required (auto-registration)
# Browse all tools
curl -s https://apibase.pro/api/v1/tools | jq '.data | length'
# Call a free tool (no payment needed)
curl -X POST https://apibase.pro/api/v1/tools/account.usage/call \
-H "Authorization: Bearer ak_live_..." \
-H "Content-Type: application/json" \
-d '{"period": "7d"}'
# Paid tool → 402 with payment instructions
curl -X POST https://apibase.pro/api/v1/tools/crypto.trending/call \
-H "Authorization: Bearer ak_live_..." \
-H "Content-Type: application/json" \
-d '{}'
500+ tools is too many for any context window. Use discover_tools prompt to find relevant tools first:
# MCP: call the discover_tools prompt
{"method": "prompts/get", "params": {"name": "discover_tools", "arguments": {"task": "search flights from NYC to London"}}}
# REST: browse categories
curl -s https://apibase.pro/api/v1/tools | jq '.data[] | select(.category == "travel")'
Most agents need 3 types of tools: browser (Playwright), docs (Context7), and real-world data (APIbase). Configure all three together:
{
"mcpServers": {
"apibase": {
"url": "https://apibase.pro/mcp",
"transport": "streamable-http"
},
"playwright": {
"command": "npx",
"args": ["-y", "@playwright/mcp"]
},
"context7": {
"command": "npx",
"args": ["-y", "@upstash/context7-mcp"]
}
}
}
Playwright = browser automation (2.3M npm/week). Context7 = up-to-date library docs (875K npm/week). APIbase = 500 real-world APIs (flights, stocks, weather, jobs, e-commerce). Each covers a different need — no overlap.
Context7 answers "how do I use this library?" — current docs, no hallucination
Playwright answers "what's on this webpage?" — screenshots, clicks, form fills
APIbase answers "what's happening in the real world?" — flight prices, stock quotes, job listings, weather, package tracking
The agent decides which server to call based on the task. No routing logic needed — the LLM reads tool descriptions and picks the right one.
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHTTP, MCPServerStdio, MCPServerManager
async with MCPServerManager(
servers=[
MCPServerStreamableHTTP(url="https://apibase.pro/mcp"),
MCPServerStdio(command="npx", args=["-y", "@playwright/mcp"]),
MCPServerStdio(command="npx", args=["-y", "@upstash/context7-mcp"]),
]
) as manager:
agent = Agent(
name="research-agent",
instructions="You have browser, docs, and 500 real-world API tools.",
mcp_servers=manager.servers
)
result = await Runner.run(agent, "Get AAPL stock price")
Base launched their official Base MCP server in May 2026 with native x402 payment support. APIbase is x402-native on Base mainnet via a self-hosted facilitator — the two pair cleanly. Base MCP signs payments from your Base Account; APIbase serves the 600+ tools your agent actually uses.
{
"mcpServers": {
"base-mcp": {
"url": "https://mcp.base.org"
},
"apibase": {
"url": "https://apibase.pro/mcp",
"transport": "streamable-http"
}
}
}
Base MCP — wallet ops, on-chain swaps (Uniswap, Aerodrome), lending (Morpho, Moonwell), perps (Avantis), and x402 payment signing. Your Base Account handles user approval per transaction.
APIbase — 600+ external API tools (flights, stocks, weather, jobs, music, chess, EV charging, food safety, government docs, …). Pay per call via x402 USDC on Base — signed by your Base Account, settled on-chain by our facilitator.
For Base App users this is the cleanest path: zero API key management (Base Account handles auth), zero per-provider signup (APIbase aggregates 191 providers), one approval flow (Base App pops up for each paid call). Compatible because both sides speak EIP-3009 transferWithAuthorization on Base mainnet.
After adding both MCP servers to your config and authenticating Base MCP:
You: "What's the current price of AAPL?" Agent: [calls APIbase finnhub.quote — gets 402 with x402 challenge] Agent: [hands payment challenge to Base MCP — user approves in Base Account popup] Agent: [retries with X-Payment header — APIbase settles on-chain via local facilitator] Agent: "AAPL is trading at $187.42 (+0.34%) as of 14:23 ET."
First paid call may take 2–3s longer than free tools (Base mainnet finality). Cache hits on the same tool within TTL skip the on-chain settle entirely — 10% of full price billed via balance debit.
async with MultiServerMCPClient({
"apibase": {"url": "https://apibase.pro/mcp", "transport": "streamable_http"},
"playwright": {"command": "npx", "args": ["-y", "@playwright/mcp"]},
"context7": {"command": "npx", "args": ["-y", "@upstash/context7-mcp"]}
}) as client:
tools = client.get_tools() # all tools from all 3 servers
agent = create_react_agent(model, tools)