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queryDocs

docs/agentic-tools/ai-sdk/tools/query-docs.mdx

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The queryDocs tool fetches documentation for a library using its Context7-compatible library ID and a query. This tool is typically called after resolveLibraryId has identified the correct library.

Usage

typescript
import { resolveLibraryId, queryDocs } 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: "How do I use React Server Components?",
  tools: {
    resolveLibraryId: resolveLibraryId(),
    queryDocs: queryDocs(),
  },
  stopWhen: stepCountIs(5),
});

Configuration

typescript
queryDocs(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 library ID and query from the model
  2. Fetches documentation from Context7's API
  3. Returns the documentation content

Input Schema

The tool accepts the following inputs from the AI model:

<ParamField path="libraryId" type="string" required> Context7-compatible library ID (e.g., `/reactjs/react.dev`, `/vercel/next.js`) </ParamField> <ParamField path="query" type="string" required> The question or task you need help with. Be specific and include relevant details. Good: "How to set up authentication with JWT in Express.js" or "React useEffect cleanup function examples". Bad: "auth" or "hooks". </ParamField>

Output Format

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

# Server Components

Server Components let you write UI that can be rendered and optionally cached on the server.

## Example

\`\`\`tsx
async function ServerComponent() {
  const data = await fetchData();
  return <div>{data}</div>;
}
\`\`\`

---

# Using Server Components with Client Components

You can import Server Components into Client Components...

On Failure

No documentation found for library "/invalid/library". This might have happened because you used an invalid Context7-compatible library ID. Use 'resolveLibraryId' to get a valid ID.

Examples

Basic Usage with Both Tools

typescript
import { resolveLibraryId, queryDocs } 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: "Show me how to set up routing in Next.js App Router",
  tools: {
    resolveLibraryId: resolveLibraryId(),
    queryDocs: queryDocs(),
  },
  stopWhen: stepCountIs(5),
});

// The model will:
// 1. Call resolveLibraryId to get the library ID
// 2. Call queryDocs({ libraryId: "/vercel/next.js", query: "routing in App Router" })
// 3. Generate a response using the fetched documentation

With Custom Configuration

typescript
import { queryDocs } from "@upstash/context7-tools-ai-sdk";

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

Direct Library ID (Skip resolveLibraryId)

If the user provides a library ID directly, the model can skip the resolution step:

typescript
import { queryDocs } 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: "Using /vercel/next.js, explain middleware",
  tools: {
    queryDocs: queryDocs(),
  },
  stopWhen: stepCountIs(3),
});

// The model recognizes the /org/project format and calls queryDocs directly

Multi-Step Documentation Lookup

For comprehensive documentation, the model can make multiple queries:

typescript
import { resolveLibraryId, queryDocs } from "@upstash/context7-tools-ai-sdk";
import { generateText, stepCountIs } from "ai";
import { anthropic } from "@ai-sdk/anthropic";

const { text } = await generateText({
  model: anthropic("claude-sonnet-4-20250514"),
  prompt: "Give me a comprehensive guide to Supabase authentication",
  tools: {
    resolveLibraryId: resolveLibraryId(),
    queryDocs: queryDocs(),
  },
  stopWhen: stepCountIs(8), // Allow more steps for multiple queries
});

// The model may call queryDocs multiple times with different queries
// to gather comprehensive documentation

Version-Specific Documentation

Library IDs can include version specifiers:

typescript
// Latest version
"/vercel/next.js";

// Specific version
"/vercel/next.js/v14.3.0-canary.87";

The model can request documentation for specific versions when the user asks about a particular version.