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Agentic Tools

Context7 provides tools and integrations that give your AI agents access to accurate, up-to-date library documentation. Instead of relying on potentially outdated training data, your agents can fetch real-time documentation to answer questions and generate code.

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Why Agentic Tools?

AI agents often struggle with:
  • Outdated knowledge - Training data becomes stale, leading to deprecated API usage
  • Hallucinated APIs - Models confidently suggest methods that don’t exist
  • Version mismatches - Code examples from old versions that no longer work
Context7’s agentic tools solve these problems by giving your agents direct access to current documentation during inference.

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Available Integrations

Vercel AI SDK

Add Context7 tools to your AI SDK workflows with generateText, streamText, or use the pre-built Context7Agent for automatic documentation lookup.

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How It Works

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Use Cases

Build chatbots that answer framework questions with accurate, version-specific information:
import { generateText, stepCountIs } from "ai";
import { openai } from "@ai-sdk/openai";
import { resolveLibraryId, queryDocs } from "@upstash/context7-tools-ai-sdk";

const { text } = await generateText({
  model: openai("gpt-5.2"),
  prompt: "How do I set up authentication in Next.js 15?",
  tools: {
    resolveLibraryId: resolveLibraryId(),
    queryDocs: queryDocs(),
  },
  stopWhen: stepCountIs(5),
});
Ensure generated code uses current APIs and best practices:
import { Context7Agent } from "@upstash/context7-tools-ai-sdk";
import { anthropic } from "@ai-sdk/anthropic";

const agent = new Context7Agent({
  model: anthropic("claude-sonnet-4-20250514"),
});

const { text } = await agent.generate({
  prompt: "Generate a Supabase Edge Function that handles webhooks",
});
Build code review agents that verify implementations against current API documentation:
import { generateText, stepCountIs } from "ai";
import { anthropic } from "@ai-sdk/anthropic";
import { resolveLibraryId, queryDocs } from "@upstash/context7-tools-ai-sdk";

const codeToReview = `
  const { data } = await supabase
    .from('users')
    .select('*')
    .eq('id', userId)
    .single();
`;

const { text } = await generateText({
  model: anthropic("claude-sonnet-4-20250514"),
  prompt: `Review this Supabase code for correctness and best practices:

${codeToReview}

Check against the latest Supabase documentation.`,
  tools: {
    resolveLibraryId: resolveLibraryId(),
    queryDocs: queryDocs(),
  },
  stopWhen: stepCountIs(5),
});

// Agent fetches current Supabase docs to verify:
// - Correct method signatures
// - Deprecated patterns
// - Security best practices
// - Error handling recommendations