---
title: Tools
description: "The Lead Agent is a tool-calling agent. Tools are how it interacts with the world: searching the web, reading and writing files, running commands, delegating tasks, and presenting outputs to the user."
---

import { Callout, Cards, Tabs } from "nextra/components";

# Tools

<Callout type="info" emoji="🔧">
  Tools are the actions the Lead Agent can take. DeerFlow provides built-in
  tools, community integrations, MCP tools, and skill tools — all controlled
  through <code>config.yaml</code>.
</Callout>

The Lead Agent is a tool-calling agent. Tools are how it interacts with the world: searching the web, reading and writing files, running commands, delegating tasks, and presenting outputs to the user.

DeerFlow organizes tools into four categories:

1. **Built-in tools** — core runtime capabilities always available to the agent
2. **Community tools** — integrations with external search, fetch, and image services
3. **MCP tools** — tools provided by external Model Context Protocol servers
4. **Skill tools** — tools bundled with specific skill packs

## Built-in tools

Built-in tools are part of the harness and do not require configuration to be available.

### task

Delegates a subtask to a subagent. The Lead Agent uses this tool when a task is too broad for a single reasoning thread or when parallel work would be beneficial.

```
task(agent="general-purpose", task="...", context="...")
```

See the [Subagents](/docs/harness/subagents) page for how subagents are configured.

---

### present_files

Presents output files to the user as artifacts. The agent calls this tool after producing a file (report, chart, code, etc.) to surface it in the conversation.

Files at `/mnt/user-data/uploads/*` are copied into `/mnt/user-data/outputs/*` before being presented. The artifact paths are tracked in `ThreadState.artifacts`.

---

### view_image

Reads an image file and injects its content into the model's context for visual analysis. Only available when the active model has `supports_vision: true`.

---

### clarification

Asks the user a clarifying question before proceeding. This is triggered by the `ClarificationMiddleware` when the model decides it does not have enough information to act.

---

### setup_agent

Dynamically configures the current agent session. Used during the bootstrap flow when setting up a new custom agent.

---

### update_agent

Persists updates to the current custom agent's `SOUL.md` and `config.yaml`. Bound to the lead agent only when a custom agent is active (`agent_name` is set in the runtime context). Use this when the user asks the agent to refine its own description, personality, skill whitelist, tool-group whitelist, or default model — it writes directly into the per-user layout `{base_dir}/users/{user_id}/agents/{agent_name}/`, so the change is picked up automatically on the next user turn. Only the fields you explicitly pass are updated; omit a field to preserve its existing value. Pass `skills=[]` to disable all skills, or omit `skills` to keep the existing whitelist.

---

### invoke_acp_agent

Invokes an external agent using the [Agent Connect Protocol (ACP)](https://agentconnectprotocol.org/). Requires `acp_agents:` configuration in `config.yaml`. See the [Subagents](/docs/harness/subagents) page for ACP configuration.

---

### tool_search

Searches for tools by name or description and loads them into the agent's context on demand. Only active when `tool_search.enabled: true` in `config.yaml`. Useful when MCP or other tool sets expose many tools and you want to reduce context usage.

## Sandbox file tools

The following tools interact with the sandbox filesystem. They require a sandbox to be configured and active.

| Tool          | Description                                                                       |
| ------------- | --------------------------------------------------------------------------------- |
| `ls`          | List files in a directory                                                         |
| `read_file`   | Read file contents                                                                |
| `glob`        | Find files matching a pattern                                                     |
| `grep`        | Search file contents                                                              |
| `write_file`  | Write content to a file                                                           |
| `str_replace` | Replace a string in a file                                                        |
| `bash`        | Execute a shell command (requires `allow_host_bash: true` or a container sandbox) |

These are configured in `config.yaml` under `tools:`:

```yaml
tools:
  - use: deerflow.sandbox.tools:ls_tool
  - use: deerflow.sandbox.tools:read_file_tool
  - use: deerflow.sandbox.tools:glob_tool
  - use: deerflow.sandbox.tools:grep_tool
  - use: deerflow.sandbox.tools:write_file_tool
  - use: deerflow.sandbox.tools:str_replace_tool
  - use: deerflow.sandbox.tools:bash_tool # requires host bash or container sandbox
```

## Community tools

Community tools connect the agent to external services. They are configured in `config.yaml` under `tools:` using the `use:` field to specify the implementation.

### Web search

<Tabs items={["DuckDuckGo (default)", "Tavily", "Exa", "InfoQuest", "Firecrawl"]}>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.ddg_search.tools:web_search_tool
```
No API key required. Default configuration. Suitable for development and general use.
  </Tabs.Tab>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.tavily.tools:web_search_tool
    api_key: $TAVILY_API_KEY
```
High-quality search with structured results. Requires a [Tavily](https://tavily.com) API key.

Install: `cd backend && uv add 'deerflow-harness[tavily]'`

  </Tabs.Tab>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.exa.tools:web_search_tool
    api_key: $EXA_API_KEY
```
Semantic search with neural retrieval. Requires an [Exa](https://exa.ai) API key.

Install: `cd backend && uv add 'deerflow-harness[exa]'`

  </Tabs.Tab>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.infoquest.tools:web_search_tool
    api_key: $INFOQUEST_API_KEY
```
InfoQuest search integration.
  </Tabs.Tab>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.firecrawl.tools:web_search_tool
    api_key: $FIRECRAWL_API_KEY
```
Firecrawl-powered search and crawl. Requires a [Firecrawl](https://firecrawl.dev) API key.

Install: `cd backend && uv add 'deerflow-harness[firecrawl]'`

  </Tabs.Tab>
</Tabs>

### Web fetch (page content extraction)

<Tabs items={["Jina AI (default)", "Exa", "InfoQuest", "Firecrawl"]}>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.jina_ai.tools:web_fetch_tool
    api_key: $JINA_API_KEY # optional; anonymous usage has rate limits
```
Converts web pages to clean Markdown. Works without an API key at reduced rate
limits.
  </Tabs.Tab>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.exa.tools:web_fetch_tool
    api_key: $EXA_API_KEY
```
  </Tabs.Tab>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.infoquest.tools:web_fetch_tool
    api_key: $INFOQUEST_API_KEY
```
  </Tabs.Tab>
  <Tabs.Tab>
```yaml
tools:
  - use: deerflow.community.firecrawl.tools:web_fetch_tool
    api_key: $FIRECRAWL_API_KEY
```
  </Tabs.Tab>
</Tabs>

### Image search

```yaml
tools:
  - use: deerflow.community.image_search.tools:image_search_tool
  # Or use InfoQuest:
  # - use: deerflow.community.infoquest.tools:image_search_tool
  #   api_key: $INFOQUEST_API_KEY
```

## Tool groups

Tool groups let you organize tools into named sets and restrict which groups a custom agent can access.

```yaml
tool_groups:
  - name: research
    tools:
      - web_search
      - web_fetch
      - image_search
  - name: coding
    tools:
      - bash
      - read_file
      - write_file
      - str_replace
      - glob
      - grep
```

Custom agents can then reference a group by name in their configuration, restricting their tool access to only the relevant set.

## Tool search (deferred loading)

When you have many tools (especially from multiple MCP servers), loading all of them upfront increases context usage and can confuse the model. The tool search feature addresses this:

```yaml
tool_search:
  enabled: true
```

When enabled, tools are not listed in the model's context directly. Instead, they are discoverable at runtime via the `tool_search` built-in tool. The agent searches by name or description and the matching tools are loaded into context on demand.

This is particularly useful when MCP servers expose dozens of tools.

<Cards num={2}>
  <Cards.Card title="MCP Integration" href="/docs/harness/mcp" />
  <Cards.Card title="Skills" href="/docs/harness/skills" />
</Cards>
