Web Context Provider with Parallel's MCP endpoint

ParallelMCPBackend speaks to Parallel’s public MCP server at https://search.parallel.ai/mcp.

Pairs with ParallelBackend (direct SDK) but is NOT equivalent: the SDK exposes web_search + web_extract, whereas the MCP server exposes web_search + web_fetch (token-efficient markdown). Pick MCP when you want the compressed markdown output, SDK when you need the raw extraction payload.

web_parallel_mcp.py

"""
Web Context Provider with Parallel's MCP endpoint
=================================================

`ParallelMCPBackend` speaks to Parallel's public MCP server at
https://search.parallel.ai/mcp — keyless by default (rate-limited),
Bearer-authenticated if `PARALLEL_API_KEY` is set.

Pairs with `ParallelBackend` (direct SDK) but is NOT equivalent: the
SDK exposes `web_search` + `web_extract`, whereas the MCP server
exposes `web_search` + `web_fetch` (token-efficient markdown). Pick
MCP when you want the compressed markdown output, SDK when you need
the raw extraction payload.

Because the backend holds an MCP session, the cookbook explicitly
brackets usage with `asetup()` / `aclose()`. In a real app those
would normally be wired into the framework's lifespan hook.

Requires:
    OPENAI_API_KEY
    (optional) PARALLEL_API_KEY raises the rate ceiling
"""

from __future__ import annotations

import asyncio

from agno.agent import Agent
from agno.context.web import ParallelMCPBackend, WebContextProvider
from agno.models.openai import OpenAIResponses


async def main() -> None:
    # ------------------------------------------------------------------
    # Create the provider (unconnected)
    # ------------------------------------------------------------------
    web = WebContextProvider(
        backend=ParallelMCPBackend(),  # reads PARALLEL_API_KEY if present; works keyless otherwise
        model=OpenAIResponses(id="gpt-5.4"),
    )

    # ------------------------------------------------------------------
    # Bracket with asetup / aclose so the MCP session lives on this task
    # ------------------------------------------------------------------
    await web.asetup()
    try:
        print(f"\nweb.status() = {web.status()}\n")

        agent = Agent(
            model=OpenAIResponses(id="gpt-5.4"),
            tools=web.get_tools(),
            instructions=web.instructions(),
            markdown=True,
        )

        prompt = "What is the latest stable release of Agno? Cite the source."
        await agent.aprint_response(prompt)
    finally:
        await web.aclose()


if __name__ == "__main__":
    asyncio.run(main())

Run the Example

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install dependencies

   uv pip install -U agno openai
   
3. Export your API keys

   Mac/Linux

   export OPENAI_API_KEY="your_openai_api_key_here"
   export PARALLEL_API_KEY="your_parallel_api_key_here"
   

   $Env:OPENAI_API_KEY="your_openai_api_key_here"
   $Env:PARALLEL_API_KEY="your_parallel_api_key_here"
   
4. Run the example

   Save the code above as web_parallel_mcp.py, then run:

   python web_parallel_mcp.py
   

Full source: cookbook/12_context/11_web_parallel_mcp.py