# PDF Vector

```json
{
  "name": "PDF Vector",
  "slug": "pdf_vector",
  "url": "https://composio.dev/toolkits/pdf_vector",
  "markdown_url": "https://composio.dev/toolkits/pdf_vector.md",
  "logo_url": "https://logos.composio.dev/api/pdf_vector",
  "categories": [
    "document & file management"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-09-10T05:32:22.575Z"
}
```

![PDF Vector logo](https://logos.composio.dev/api/pdf_vector)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with PDF Vector MCP or direct API to parse PDFs into markdown, extract structured data, answer document questions, and search academic publications and grants through natural language.

## Summary

PDF Vector is a document parsing and vector-search service that converts PDFs into markdown and structured data.
Use it to quickly find, extract, and index details from academic papers and grant documents.

## Categories

- document & file management

## Toolkit Details

- Tools: 10

## Images

- Logo: https://logos.composio.dev/api/pdf_vector

## Authentication

- **Api Key**
  - Type: `api_key`
  - Description: Api Key authentication for PDF Vector.
  - Setup:
    - Configure Api Key credentials for PDF Vector.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- Summarize key findings from research paper
- Extract tables from grant PDF into JSON
- Search similar publications for this abstract

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PDF_VECTOR_ASK_DOCUMENT` | Ask Document | Answer one question from a general, identity, invoice, or bank-statement document. Processing consumes credits; the response reports the actual model and credit cost. The tool never retries with a higher model automatically. |
| `PDF_VECTOR_EXTRACT_DOCUMENT` | Extract Document Data | Extract schema-constrained structured data from a general, identity, invoice, or bank-statement document. Processing consumes credits and never retries with a higher model automatically. |
| `PDF_VECTOR_FETCH_PUBLICATIONS` | Fetch Publications | Resolve up to 100 publication identifiers with provider auto-detection and return both resolved records and per-identifier errors. |
| `PDF_VECTOR_FIND_CITATIONS` | Find Citations | Find relevant academic citations for each sentence in a paragraph and preserve provider-specific partial errors. |
| `PDF_VECTOR_FIND_SIMILAR_PAPERS` | Find Similar Papers | Find papers related to a seed publication using citation-network similarity, optionally including relationship edges. |
| `PDF_VECTOR_GET_PAPER_GRAPH` | Get Paper Graph | Retrieve a publication plus one independently offset-controlled page of citing papers and one page of referenced papers. |
| `PDF_VECTOR_PARSE_ACADEMIC_PAPER` | Parse Academic Paper | Resolve an academic identifier or provider URL to a public PDF and parse it to markdown. Processing consumes credits, returns the actual model and credit cost, and never retries with a higher model automatically. |
| `PDF_VECTOR_PARSE_DOCUMENT` | Parse Document | Convert a general, identity, invoice, or bank-statement document to markdown. Processing consumes credits; returns the actual model and credit cost and never retries with a higher model automatically. |
| `PDF_VECTOR_SEARCH_PUBLICATIONS` | Search Publications | Search academic publications across selected databases and return one offset-controlled page, including any provider-specific partial errors. |
| `PDF_VECTOR_SEARCH_RESEARCH_GRANTS` | Search Research Grants | Search US, EU, and UK research-grant providers and return one explicit offset-controlled page with partial provider errors. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK
```python
pip install composio_openai
```

```typescript
npm install @composio/openai
```

#### Path 1, Step 2: Initialize Composio and Create Tool Router Session

Import and initialize Composio client, then create a Tool Router session
```python
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
openai = OpenAI()
session = composio.create(user_id='your-user-id')
```

```typescript
import OpenAI from 'openai';
import { Composio } from '@composio/core';
import { OpenAIResponsesProvider } from '@composio/openai';

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');
```

#### Path 1, Step 3: Execute PDF Vector Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute PDF Vector actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'YOUR_SPECIFIC_PROMPT_HERE'
  }]
)
result = composio.provider.handle_tool_calls(
  response=response,
  user_id='your-user-id'
)
print(result)
```

```typescript
const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'YOUR_SPECIFIC_PROMPT_HERE'
  }],
});
const result = await composio.provider.handleToolCalls(
  'your-user-id',
  response.output
);
console.log(result);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK for Python or TypeScript
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
```

#### Path 2, Step 2: Initialize Client and Create Tool Router Session

Import and initialize the Composio client, then create a Tool Router session for PDF Vector
```python
from composio import Composio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

composio = Composio(api_key='your-composio-api-key')
session = composio.create(user_id='your-user-id')
url = session.mcp.url
```

```typescript
import { Composio } from '@composio/core';

const composio = new Composio({ apiKey: 'your-api-key' });
const session = await composio.create('your-user-id');
console.log(`Tool Router session created: ${session.mcp.url}`);
```

#### Path 2, Step 3: Connect to AI Agent

Use the MCP server with your AI agent (Anthropic Claude or Mastra)
```python
import asyncio

options = ClaudeAgentOptions(
    permission_mode='bypassPermissions',
    mcp_servers={
        'tool_router': {
            'type': 'http',
            'url': url,
            'headers': {
                'x-api-key': 'your-composio-api-key'
            }
        }
    },
    system_prompt='You are a helpful assistant with access to PDF Vector tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('YOUR_SPECIFIC_PROMPT_HERE')
        async for message in client.receive_response():
            if hasattr(message, 'content'):
                for block in message.content:
                    if hasattr(block, 'text'):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { openai } from '@ai-sdk/openai';
import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp';
import { generateText } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: session.mcp.url,
    headers: {
      'x-api-key': 'your-composio-api-key',
    },
  },
});

const tools = await client.tools();
const { text } = await generateText({
  model: openai('gpt-4o'),
  tools,
  messages: [{
    role: 'user',
    content: 'YOUR_SPECIFIC_PROMPT_HERE'
  }],
  maxSteps: 5,
});

console.log(`Agent: ${text}`);
```

## Why Use Composio?

### 1. AI Native PDF Vector Integration

- Supports both PDF Vector MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable tool execution
- Rich coverage for reading, writing, and querying your PDF Vector data

### 2. Managed Auth

- Built-in OAuth handling with automatic token refresh and rotation
- Central place to manage, scope, and revoke PDF Vector access
- Per user and per environment credentials instead of hard-coded keys

### 3. Agent Optimized Design

- Tools are tuned using real error and success rates to improve reliability over time
- Comprehensive execution logs so you always know what ran, when, and on whose behalf

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access PDF Vector
- Scoped, least privilege access to PDF Vector resources
- Full audit trail of agent actions to support review and compliance

## Use PDF Vector with any AI Agent Framework

Choose a framework you want to connect PDF Vector with:

- [ChatGPT Work](https://composio.dev/toolkits/pdf_vector/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/pdf_vector/framework/claude-cowork)
- [Hermes](https://composio.dev/toolkits/pdf_vector/framework/hermes-agent)

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## Frequently Asked Questions

### Do I need my own developer credentials to use PDF Vector with Composio?

Yes, PDF Vector requires you to configure your own API key credentials. Once set up, Composio handles secure credential storage and API request handling for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
