> ## Documentation Index
> Fetch the complete documentation index at: https://context7.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# resolveLibraryId

> Search for libraries and resolve them to Context7-compatible IDs

The `resolveLibraryId` tool searches Context7's library database and returns matching results with their Context7-compatible library IDs. This is typically the first step in a documentation lookup workflow.

## Usage

```typescript theme={null}
import { resolveLibraryId } from "@upstash/context7-tools-ai-sdk";
import { generateText, stepCountIs } from "ai";
import { openai } from "@ai-sdk/openai";

const { text } = await generateText({
  model: openai("gpt-5.2"),
  prompt: "Find documentation for React hooks",
  tools: {
    resolveLibraryId: resolveLibraryId(),
  },
  stopWhen: stepCountIs(3),
});
```

## Configuration

```typescript theme={null}
resolveLibraryId(config?: Context7ToolsConfig)
```

### Parameters

<ParamField path="config" type="Context7ToolsConfig" optional>
  Configuration options for the tool.

  <Expandable title="properties">
    <ParamField path="apiKey" type="string" optional>
      Context7 API key. If not provided, uses the `CONTEXT7_API_KEY` environment variable.
    </ParamField>
  </Expandable>
</ParamField>

### Returns

Returns an AI SDK `tool` that can be used with `generateText`, `streamText`, or agents.

## Tool Behavior

When the AI model calls this tool, it:

1. Takes a `query` and `libraryName` parameter from the model
2. Searches Context7's database for matching libraries
3. Returns formatted results including:
   * Library ID (e.g., `/reactjs/react.dev`)
   * Title and description
   * Number of code snippets available
   * Source reputation score
   * Available versions

### Input Schema

The tool accepts the following input from the AI model:

<ParamField path="query" type="string" required>
  The user's original question or task. This is used to rank library results by relevance to what the user is trying to accomplish.
</ParamField>

<ParamField path="libraryName" type="string" required>
  Library name to search for (e.g., "react", "next.js", "vue")
</ParamField>

### Output Format

On success, the tool returns the search results as plain text, formatted for easy consumption by the AI model:

```
- Title: React Documentation
- Context7-compatible library ID: /reactjs/react.dev
- Description: The library for web and native user interfaces
- Code Snippets: 1250
- Trust Score: High
- Benchmark Score: 98
- Versions: 19.0.0, 18.3.1, 18.2.0
----------
- Title: React Native
- Context7-compatible library ID: /facebook/react-native
- Description: A framework for building native applications using React
- Code Snippets: 890
- Trust Score: High
- Benchmark Score: 95
- Versions: 0.76.0, 0.75.4
```

On failure:

```
No libraries found matching "unknown-lib". Try a different search term or check the library name.
```

## Examples

### Basic Usage

```typescript theme={null}
import { resolveLibraryId, queryDocs } from "@upstash/context7-tools-ai-sdk";
import { generateText, stepCountIs } from "ai";
import { openai } from "@ai-sdk/openai";

const { text, toolCalls } = await generateText({
  model: openai("gpt-5.2"),
  prompt: "What libraries are available for React?",
  tools: {
    resolveLibraryId: resolveLibraryId(),
    queryDocs: queryDocs(),
  },
  stopWhen: stepCountIs(5),
});

// The model will call resolveLibraryId and receive a list of matching libraries
console.log(text);
```

### With Custom API Key

```typescript theme={null}
import { resolveLibraryId } from "@upstash/context7-tools-ai-sdk";

const tool = resolveLibraryId({
  apiKey: process.env.CONTEXT7_API_KEY,
});
```

### Inspecting Tool Calls

```typescript theme={null}
import { resolveLibraryId } from "@upstash/context7-tools-ai-sdk";
import { generateText, stepCountIs } from "ai";
import { openai } from "@ai-sdk/openai";

const { toolCalls, toolResults } = await generateText({
  model: openai("gpt-5.2"),
  prompt: "Find the official Next.js documentation",
  tools: {
    resolveLibraryId: resolveLibraryId(),
  },
  stopWhen: stepCountIs(3),
});

// See what the model searched for
for (const call of toolCalls) {
  console.log("Searched for:", call.args.libraryName);
}

// See the results
for (const result of toolResults) {
  console.log("Found:", result.result);
}
```

## Selection Guidance

The tool's description instructs the AI model to select libraries based on:

1. **Name similarity** - Exact matches are prioritized
2. **Description relevance** - How well the description matches the query intent
3. **Documentation coverage** - Libraries with more code snippets are preferred
4. **Source reputation** - High/Medium reputation sources are more authoritative
5. **Benchmark score** - Quality indicator (100 is the highest)

## Related

* [queryDocs](/agentic-tools/ai-sdk/tools/query-docs) - Fetch documentation using the resolved library ID
* [Context7Agent](/agentic-tools/ai-sdk/agents/context7-agent) - Pre-built agent that handles the full workflow