parallel-google-adk

Google Agent Development Kit (ADK) tools and plugin for Parallel — grounded web search, clean extraction, and cited deep research with structured output.

Install

pip install parallel-google-adk
export PARALLEL_API_KEY=your-key-here  # get one at https://platform.parallel.ai

Quickstart

import os
from google.adk.agents import LlmAgent
from google.adk.runners import Runner

from parallel_google_adk import (
    web_search, web_fetch, extract,
    deep_research, enrich,
    ParallelTracingPlugin,
)

agent = LlmAgent(
    model="gemini-flash-latest",
    name="research_agent",
    instruction=(
        "You are a research assistant. Use web_search to find sources, "
        "web_fetch or extract for specific URLs, and deep_research for "
        "comprehensive cited reports."
    ),
    tools=[web_search, web_fetch, extract, deep_research, enrich],
)

# Plugins attach to the Runner, not the agent.
runner = Runner(agent=agent, app_name="my-app", plugins=[ParallelTracingPlugin()])

Tools

Tool What it does
web_search Grounded web search returning citation-aware excerpts.
web_fetch Clean content from a single URL. Handles JS and PDFs.
extract Batch extraction across 1–20 URLs with optional objective.
deep_research Multi-hop investigation with per-claim citations. Returns a markdown report.
enrich Structured (JSON-Schema-conforming) enrichment of a list of entities.

Plugin

ParallelTracingPlugin records latency, citation count, and (when reported) cost for every Parallel tool call. Read the trace from tool_context.state["_parallel_calls"].

MCP alternative

If you only want Search and don't want a Python dependency, the Parallel Search MCP works with ADK's MCPToolset:

import os
from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams

MCPToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://search.parallel.ai/mcp",
        headers={"Authorization": f"Bearer {os.environ['PARALLEL_API_KEY']}"},
    ),
)

This package is the typed-FunctionTool path for users who want fine-grained schemas, hidden polling, structured enrichment, and tracing.

Examples

See examples/research_agent.py for a runnable demo.

Development

pip install -e ".[dev]"
pytest                              # unit tests (no network)
pytest tests/integration/           # live API smoke (needs PARALLEL_API_KEY + GOOGLE_API_KEY)

License

MIT

Project links

Data verified by PyPI on Apr 30, 2026
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Credits

Author: Parallel

GitHub Statistics

Data verified by PyPI on Apr 30, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT)

Requires

Python >=3.10

Provides Extra

dev

Tags

ai-agents google-adk parallel rag research web-search

Classifiers

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