# ToolSearchProcessor

The `ToolSearchProcessor` is an **input processor** that enables dynamic tool discovery and loading. Instead of providing all tools to the agent upfront, it gives the agent two meta-tools (`search_tools` and `load_tool`) that let it find and load tools on demand. This reduces context token usage when working with large tool libraries.

## Usage example

```typescript
import { ToolSearchProcessor } from "@mastra/core/processors";

const toolSearch = new ToolSearchProcessor({
  tools: {
    createIssue: githubTools.createIssue,
    sendEmail: emailTools.send,
    getWeather: weatherTools.forecast,
    // ... many more tools
  },
  search: {
    topK: 5,
    minScore: 0.1,
  },
});
```

## Constructor parameters

**options:** (`ToolSearchProcessorOptions`): Configuration options for the tool search processor

### Options

**tools:** (`Record<string, Tool>`): All tools that can be searched and loaded dynamically. These tools are not immediately available to the agent — they must be discovered via search and loaded on demand.

**search?:** (`{ topK?: number; minScore?: number }`): Configuration for the search behavior.

**search.topK?:** (`number`): Maximum number of tools to return in search results.

**search.minScore?:** (`number`): Minimum relevance score (0-1) for including a tool in search results.

**ttl?:** (`number`): Time-to-live for thread state in milliseconds. After this duration of inactivity, thread state will be cleaned up. Set to 0 to disable cleanup.

## Returns

**id:** (`string`): Processor identifier set to 'tool-search'

**name:** (`string`): Processor display name set to 'Tool Search Processor'

**processInputStep:** (`(args: ProcessInputStepArgs) => Promise<ProcessInputStepResult>`): Processes each step to inject search/load meta-tools and any previously loaded tools into the agent's tool set.

## Extended usage example

```typescript
import { Agent } from "@mastra/core/agent";
import { ToolSearchProcessor } from "@mastra/core/processors";

// Tools from various integrations
import { githubTools } from "./tools/github";
import { slackTools } from "./tools/slack";
import { dbTools } from "./tools/database";

const toolSearch = new ToolSearchProcessor({
  tools: {
    ...githubTools,  // createIssue, listPRs, mergePR, ...
    ...slackTools,   // sendMessage, createChannel, ...
    ...dbTools,      // query, insert, update, ...
  },
  search: {
    topK: 5,
    minScore: 0.1,
  },
});

const agent = new Agent({
  name: "dynamic-tools-agent",
  instructions: "You are a helpful assistant with access to many tools. Use search_tools to find relevant tools, then load_tool to make them available.",
  model: "openai/gpt-4o",
  inputProcessors: [toolSearch],
});
```

The agent workflow is:

1. Agent receives a user message
2. Agent calls `search_tools` with keywords (e.g., "github issue")
3. Agent reviews results and calls `load_tool` with the tool name
4. The loaded tool becomes available on the next turn
5. Agent uses the loaded tool normally

## Combining with other processors

```typescript
import { Agent } from "@mastra/core/agent";
import {
  ToolSearchProcessor,
  TokenLimiter,
} from "@mastra/core/processors";

const agent = new Agent({
  name: "my-agent",
  model: "openai/gpt-4o",
  inputProcessors: [
    new ToolSearchProcessor({
      tools: allTools,
      search: { topK: 5 },
    }),
    // Place TokenLimiter last to ensure context fits
    new TokenLimiter(127000),
  ],
});
```

## Related

- [Processors](https://mastra.ai/docs/agents/processors)
- [Using Tools](https://mastra.ai/docs/agents/using-tools)