---
title: "Context7Agent"
sidebarTitle: "Context7Agent"
description: "Pre-built AI agent for documentation lookup workflows"
---
The `Context7Agent` class is a pre-configured AI agent that handles the complete documentation lookup workflow automatically. It combines both `resolveLibraryId` and `queryDocs` tools with an optimized system prompt.
## Usage
```typescript
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: "How do I use React Server Components?",
});
console.log(text);
```
## Configuration
```typescript
new Context7Agent(config?: Context7AgentConfig)
```
### Parameters
<ParamField path="config" type="Context7AgentConfig" optional>
Configuration options for the agent.
<Expandable title="properties">
<ParamField path="model" type="LanguageModel" optional>
Language model to use. Must be a LanguageModel instance from an AI SDK provider.
Examples:
- `anthropic('claude-sonnet-4-20250514')`
- `openai('gpt-5.2')`
- `google('gemini-1.5-pro')`
</ParamField>
<ParamField path="apiKey" type="string" optional>
Context7 API key. If not provided, uses the `CONTEXT7_API_KEY` environment variable.
</ParamField>
<ParamField path="system" type="string" optional>
Custom system prompt. Overrides the default `AGENT_PROMPT`.
</ParamField>
<ParamField path="stopWhen" type="StopCondition" optional default="stepCountIs(5)">
Condition for when the agent should stop. Defaults to stopping after 5 steps.
</ParamField>
</Expandable>
</ParamField>
### Returns
`Context7Agent` extends the AI SDK `Agent` class and provides `generate()` and `stream()` methods.
## Agent Workflow
The agent follows a structured multi-step workflow:
```mermaid
flowchart TD
A[User Query] --> B[Extract Library Name]
B --> C[Call resolveLibraryId]
C --> D{Results Found?}
D -->|Yes| E[Select Best Match]
D -->|No| F[Report No Results]
E --> G[Call queryDocs]
G --> H{Sufficient Context?}
H -->|Yes| I[Generate Response]
H -->|No| J[Fetch More Docs]
J --> H
I --> K[Return Answer with Examples]
```
### Step-by-Step
1. **Extract library name** - Identifies the library/framework from the user's query
2. **Resolve library** - Calls `resolveLibraryId` to find the Context7 library ID
3. **Select best match** - Analyzes results based on reputation, coverage, and relevance
4. **Fetch documentation** - Calls `queryDocs` with the selected library ID and user's query
5. **Query if needed** - Makes additional queries if initial context is insufficient
6. **Generate response** - Provides an answer with code examples from the documentation
## Examples
### Basic Usage
```typescript
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: "How do I set up authentication in Next.js?",
});
console.log(text);
```
### With OpenAI
```typescript
import { Context7Agent } from "@upstash/context7-tools-ai-sdk";
import { openai } from "@ai-sdk/openai";
const agent = new Context7Agent({
model: openai("gpt-5.2"),
});
const { text } = await agent.generate({
prompt: "Explain Tanstack Query's useQuery hook",
});
```
### Streaming Responses
```typescript
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 { textStream } = await agent.stream({
prompt: "How do I create a Supabase Edge Function?",
});
for await (const chunk of textStream) {
process.stdout.write(chunk);
}
```
### Custom Configuration
```typescript
import { Context7Agent } from "@upstash/context7-tools-ai-sdk";
import { anthropic } from "@ai-sdk/anthropic";
import { stepCountIs } from "ai";
const agent = new Context7Agent({
model: anthropic("claude-sonnet-4-20250514"),
apiKey: process.env.CONTEXT7_API_KEY,
stopWhen: stepCountIs(8), // Allow more steps for complex queries
});
```
### Custom System Prompt
```typescript
import { Context7Agent, AGENT_PROMPT } from "@upstash/context7-tools-ai-sdk";
import { openai } from "@ai-sdk/openai";
const agent = new Context7Agent({
model: openai("gpt-5.2"),
system: `${AGENT_PROMPT}
Additional instructions:
- Always include TypeScript examples
- Mention version compatibility when relevant
- Suggest related documentation topics`,
});
```
## Comparison: Agent vs Tools
| Feature | Context7Agent | Individual Tools |
| ------------- | -------------------- | -------------------- |
| Setup | Single configuration | Configure each tool |
| Workflow | Automatic multi-step | Manual orchestration |
| System prompt | Optimized default | You provide |
| Customization | Limited | Full control |
| Best for | Quick integration | Custom workflows |
### When to Use the Agent
- Rapid prototyping
- Standard documentation lookup use cases
- When you want sensible defaults
### When to Use Individual Tools
- Custom agentic workflows
- Integration with other tools
- Fine-grained control over the process
- Custom system prompts with specific behavior
## Related
- [resolveLibraryId](/agentic-tools/ai-sdk/tools/resolve-library-id) - The library search tool used by the agent
- [queryDocs](/agentic-tools/ai-sdk/tools/query-docs) - The documentation fetch tool used by the agent
- [Getting Started](/agentic-tools/ai-sdk/getting-started) - Overview of the AI SDK integration
