ag2-use-builtin-tools

name	ag2-use-builtin-tools
description	Wire AG2 beta's shipped tools into an `Agent` — both provider-native server-side tools (web search, web fetch, code execution, MCP, image generation, memory) and locally-executed common toolkits (filesystem, DuckDuckGo, Exa, Tavily, skills). Use when the user wants capabilities AG2 already ships rather than writing custom Python. For shell commands see `ag2-shell-tool`; for custom Python tools see `ag2-add-custom-tool`.
license	Apache-2.0

Use AG2 beta's built-in tools

When to use

Reach for this skill when the user wants to add a capability that AG2 already ships. Two families:

1. Provider-native tools (autogen.beta.tools — WebSearchTool, CodeExecutionTool, etc.) — executed server-side by Anthropic / OpenAI / Gemini. No Python implementation on your side.
2. Common toolkits (autogen.beta.tools — FilesystemToolkit, DuckDuckSearchTool, ExaToolkit, TavilySearchTool, SkillsToolkit) — regular Python that runs in your process and works with every provider.

For shell commands, use ag2-shell-tool (it's important enough to live in its own skill). For custom Python tools, use ag2-add-custom-tool.

60-second recipes

Web search (provider-native)

from autogen.beta import Agent
from autogen.beta.config import AnthropicConfig
from autogen.beta.tools import WebSearchTool, UserLocation

agent = Agent(
    "researcher",
    config=AnthropicConfig(model="claude-sonnet-4-6"),
    tools=[
        WebSearchTool(
            max_uses=5,
            user_location=UserLocation(country="US"),
            allowed_domains=["github.com", "pypi.org"],
            blocked_domains=["pinterest.com"],
        ),
    ],
)

Web fetch (Anthropic / Gemini only)

from autogen.beta.tools import WebFetchTool

tools = [WebFetchTool(max_uses=3, max_content_tokens=50000, citations=True)]

Code execution

from autogen.beta.tools import CodeExecutionTool

agent = Agent("analyst", config=config, tools=[CodeExecutionTool()])

MCP server integration

from autogen.beta.tools import MCPServerTool

tools = [
    MCPServerTool(
        server_url="https://mcp.example.com/sse",
        server_label="my-tools",
        allowed_tools=["search", "summarize"],
    ),
]

Image generation (OpenAI Responses only)

from autogen.beta.config import OpenAIResponsesConfig
from autogen.beta.tools import ImageGenerationTool

agent = Agent(
    "designer",
    config=OpenAIResponsesConfig(model="gpt-4.1"),
    tools=[ImageGenerationTool(quality="high", size="1024x1024", output_format="png")],
)
reply = await agent.ask("Generate a logo for a coffee shop.")
images: list[bytes] = reply.images

Filesystem (sandboxed, any provider)

from autogen.beta.tools import FilesystemToolkit

fs = FilesystemToolkit(base_path="/tmp/workspace")
agent = Agent("worker", config=config, tools=[fs])

base_path is enforced — ../../etc/passwd raises PermissionError. Use read_only=True to expose only read_file and find_files. For ephemeral workspaces use tempfile.TemporaryDirectory() rather than hardcoding /tmp.

Web search via DuckDuckGo (no API key)

from autogen.beta.tools import DuckDuckSearchTool
# requires: pip install ag2[ddgs]

tools = [DuckDuckSearchTool(max_results=10, region="us-en", safesearch="moderate")]

Exa neural search

import os
from autogen.beta.tools import ExaToolkit
# requires: pip install ag2[exa]

tools = [ExaToolkit(api_key=os.environ["EXA_API_KEY"])]

Each tool is exposed as a factory method (exa.search(), exa.find_similar(), exa.get_contents(), exa.answer()) so you can pass only what you need with per-call config.

Tavily search

import os
from autogen.beta.tools import TavilySearchTool
# requires: pip install ag2[tavily]

tools = [TavilySearchTool(
    api_key=os.environ["TAVILY_API_KEY"],
    search_depth="advanced",
    include_answer=True,
)]

Going deeper

• Per-tool provider support, every parameter, version pinning — references/builtin_tools_matrix.md.
• Source docs — website/docs/beta/tools/builtin_tools.mdx (provider-native), website/docs/beta/tools/common_toolkits.mdx (common toolkits — also covers SkillsToolkit and SkillSearchToolkit).
• Toolkits authoring — website/docs/beta/tools/toolkits.mdx.

Common pitfalls

• Mismatch between tool and provider — WebFetchTool raises with OpenAI; MemoryTool is Anthropic-only; ImageGenerationTool is OpenAI Responses only. Check references/builtin_tools_matrix.md first.
• Anthropic tool versions default to older revisions — pin version="web_search_20260209" etc. when you need dynamic filtering on Opus 4.6 / Sonnet 4.6.
• FilesystemToolkit paths are sandboxed — by design. Don't try to bypass the path-traversal guard; choose a wider base_path instead.
• Toolkits and individual tools mix freely — tools=[fs, exa, my_custom_tool] is fine.
• Optional dependency missing — DuckDuckSearchTool, ExaToolkit, TavilySearchTool need their ag2[<extra>] install. Without it you get a clear ImportError from the config-fallback layer, not a confusing crash.