Connect to remote MCP safely You authorize remote MCP with OAuth, client credentials, or enterprise policy while keeping application identity separate. URL validation and SSRF protections stay enabled. cpp academy academy/topics/mcp-auth-security website/content-src/academy/course.mjs academy Connect to remote MCP safely
Unit 9 · Connect to external tools and data

Connect to remote MCP safely

You authorize remote MCP with OAuth, client credentials, or enterprise policy while keeping application identity separate. URL validation and SSRF protections stay enabled.

10 focused minutesNot started
Unit example (nearest native match)

See the idea in context

auto transport = std::make_shared<axllm::AxMCPStreamableHTTPTransport>(endpoint);
auto mcp = std::make_shared<axllm::AxMCPClient>(transport, axllm::object({{"namespace", "inventory"}}));
axllm::AxExecutionContext context({mcp});
auto program = axllm::ax("request:string -> answer:string");
context.attach(program);
axllm::OpenAICompatibleClient llm(axllm::object({
  {"api_key", key}, {"model", "gpt-5.4-mini"},
}));
auto catalog = mcp->inspect_catalog();
std::cout << "MCP catalog: " << axllm::Core::iter(catalog.tools).size()
          << " tools, " << axllm::Core::iter(catalog.resources).size()
          << " resources\n";
std::cout << axllm::stringify(program.forward(
  llm, axllm::object({{"request", "Reindex inventory."}})
)) << "\n";
mcp->close();
Run itIn your own project
cmake_minimum_required(VERSION 3.20)
project(ax_quick_start LANGUAGES CXX)
set(CMAKE_CXX_STANDARD 17)

include(FetchContent)
FetchContent_Declare(axllm GIT_REPOSITORY https://github.com/ax-llm/ax GIT_TAG main SOURCE_SUBDIR packages/cpp)
FetchContent_MakeAvailable(axllm)

add_executable(quick_start quick_start.cpp)
target_link_libraries(quick_start PRIVATE axllm::axllm)

#include <axllm/axllm.hpp>
#include <cstdlib>
#include <iostream>

int main() {
  auto llm = axllm::ai("openai", axllm::object({{"apiKey", std::getenv("OPENAI_API_KEY")}}));
  auto classify = axllm::ax("review:string -> sentiment:class \"positive, negative, neutral\"");
  auto result = classify.forward(*llm, axllm::object({
    {"review", "Useful and boring in the best way."}
  }));

  auto sentiment = axllm::Core::get(result, "sentiment");
  std::cout << "sentiment: " << std::get<std::string>(sentiment.data) << "\n";
}

Set OPENAI_APIKEY in your environment before running provider-backed code.

In the ax repo

From a clone of the ax repo:

npm run example -- cpp src/examples/cpp/mcp/native_mcp_tools.cpp
Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1
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