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 exampleDirect link to Usage example
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 parametersDirect link to Constructor parameters
options:
ToolSearchProcessorOptions
Configuration options for the tool search processor
OptionsDirect link to 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.
ReturnsDirect link to 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 exampleDirect link to Extended usage example
src/mastra/agents/dynamic-tools-agent.ts
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:
- Agent receives a user message
- Agent calls
search_toolswith keywords (e.g., "github issue") - Agent reviews results and calls
load_toolwith the tool name - The loaded tool becomes available on the next turn
- Agent uses the loaded tool normally
Combining with other processorsDirect link to Combining with other processors
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),
],
})