Content
# DeepResearch MCP
<div align="center">
[](https://www.typescriptlang.org/)
[](https://openai.com/)
[](https://nodejs.org/)
</div>
## 📚 Overview
DeepResearch MCP is a powerful research assistant built on the Model Context Protocol (MCP). It conducts intelligent, iterative research on any topic through web searches, analysis, and comprehensive report generation.
### 🌟 Key Features
- **Intelligent Topic Exploration** - Automatically identifies knowledge gaps and generates focused search queries
- **Comprehensive Content Extraction** - Enhanced web scraping with improved content organization
- **Structured Knowledge Processing** - Preserves important information while managing token usage
- **Scholarly Report Generation** - Creates detailed, well-structured reports with executive summaries, analyses, and visualizations
- **Complete Bibliography** - Properly cites all sources with numbered references
- **Adaptive Content Management** - Automatically manages content to stay within token limits
- **Error Resilience** - Recovers from errors and generates partial reports when full processing isn't possible
## 🛠️ Architecture
<div align="center">
```
┌────────────────────┐ ┌─────────────────┐ ┌────────────────┐
│ │ │ │ │ │
│ MCP Server Layer ├────►│ Research Service├────►│ Search Service │
│ (Tools & Prompts) │ │ (Session Mgmt) │ │ (Firecrawl) │
│ │ │ │ │ │
└────────────────────┘ └─────────┬───────┘ └────────────────┘
│
▼
┌─────────────────┐
│ │
│ OpenAI Service │
│ (Analysis/Rpt) │
│ │
└─────────────────┘
```
</div>
## 💻 Installation
### Prerequisites
- Node.js 18 or higher
- OpenAI API key
- Firecrawl API key
### Setup Steps
1. **Clone the repository**
```bash
git clone <repository-url>
cd deep-research-mcp
```
2. **Install dependencies**
```bash
npm install
```
3. **Configure environment variables**
```bash
cp .env.example .env
```
Edit the `.env` file and add your API keys:
```
OPENAI_API_KEY=sk-your-openai-api-key
FIRECRAWL_API_KEY=your-firecrawl-api-key
```
4. **Build the project**
```bash
npm run build
```
## 🚀 Usage
### Running the MCP Server
Start the server on stdio for MCP client connections:
```bash
npm start
```
### Using the Example Client
Run research on a specific topic with a specified depth:
```bash
npm run client "Your research topic" 3
```
Parameters:
- First argument: Research topic or query
- Second argument: Research depth (number of iterations, default: 2)
- Third argument (optional): "complete" to use the complete-research tool (one-step process)
Example:
```bash
npm run client "the impact of climate change on coral reefs" 3 complete
```
### Example Output
The DeepResearch MCP will produce a comprehensive report that includes:
- **Executive Summary** - Concise overview of the research findings
- **Introduction** - Context and importance of the research topic
- **Methodology** - Description of the research approach
- **Comprehensive Analysis** - Detailed examination of the topic
- **Comparative Analysis** - Visual comparison of key aspects
- **Discussion** - Interpretation of findings and implications
- **Limitations** - Constraints and gaps in the research
- **Conclusion** - Final insights and recommendations
- **Bibliography** - Complete list of sources with URLs
## 🔧 MCP Integration
### Available MCP Resources
| Resource Path | Description |
|--------------|-------------|
| `research://state/{sessionId}` | Access the current state of a research session |
| `research://findings/{sessionId}` | Access the collected findings for a session |
### Available MCP Tools
| Tool Name | Description | Parameters |
|-----------|-------------|------------|
| `initialize-research` | Start a new research session | `query`: string, `depth`: number |
| `execute-research-step` | Execute the next research step | `sessionId`: string |
| `generate-report` | Create a final report | `sessionId`: string, `timeout`: number (optional) |
| `complete-research` | Execute the entire research process | `query`: string, `depth`: number, `timeout`: number (optional) |
## 🖥️ Claude Desktop Integration
DeepResearch MCP can be integrated with Claude Desktop to provide direct research capabilities to Claude.
### Configuration Steps
1. **Copy the sample configuration**
```bash
cp claude_desktop_config_sample.json ~/path/to/claude/desktop/config/directory/claude_desktop_config.json
```
2. **Edit the configuration file**
Update the path to point to your installation of deep-research-mcp and add your API keys:
```json
{
"mcpServers": {
"deep-research": {
"command": "node",
"args": [
"/absolute/path/to/your/deep-research-mcp/dist/index.js"
],
"env": {
"FIRECRAWL_API_KEY": "your-firecrawler-api-key",
"OPENAI_API_KEY": "your-openai-api-key"
}
}
}
}
```
3. **Restart Claude Desktop**
After saving the configuration, restart Claude Desktop for the changes to take effect.
4. **Using with Claude Desktop**
Now you can ask Claude to perform research using commands like:
```
Can you research the impact of climate change on coral reefs and provide a detailed report?
```
## 📋 Sample Client Code
```typescript
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
async function main() {
// Connect to the server
const transport = new StdioClientTransport({
command: "node",
args: ["dist/index.js"]
});
const client = new Client({ name: "deep-research-client", version: "1.0.0" });
await client.connect(transport);
// Initialize research
const initResult = await client.callTool({
name: "initialize-research",
arguments: {
query: "The impact of artificial intelligence on healthcare",
depth: 3
}
});
// Parse the response to get sessionId
const { sessionId } = JSON.parse(initResult.content[0].text);
// Execute steps until complete
let currentDepth = 0;
while (currentDepth < 3) {
const stepResult = await client.callTool({
name: "execute-research-step",
arguments: { sessionId }
});
const stepInfo = JSON.parse(stepResult.content[0].text);
currentDepth = stepInfo.currentDepth;
console.log(`Completed step ${stepInfo.currentDepth}/${stepInfo.maxDepth}`);
}
// Generate final report with timeout
const report = await client.callTool({
name: "generate-report",
arguments: {
sessionId,
timeout: 180000 // 3 minutes timeout
}
});
console.log("Final Report:");
console.log(report.content[0].text);
}
main().catch(console.error);
```
## 🔍 Troubleshooting
### Common Issues
- **Token Limit Exceeded**: For very large research topics, you may encounter OpenAI token limit errors. Try:
- Reducing the research depth
- Using more specific queries
- Breaking complex topics into smaller sub-topics
- **Timeout Errors**: For complex research, the process may time out. Solutions:
- Increase the timeout parameters in tool calls
- Use the `complete-research` tool with a longer timeout
- Process research in smaller chunks
- **API Rate Limits**: If you encounter rate limit errors from OpenAI or Firecrawl:
- Implement a delay between research steps
- Use an API key with higher rate limits
- Retry with exponential backoff
## 📝 License
ISC
## 🙏 Acknowledgements
- Built with [Model Context Protocol](https://github.com/mhuggins7278/model-context-protocol)
- Powered by [OpenAI](https://openai.com/) and [Firecrawl](https://firecrawl.dev/)
