Ollama Deep Researcher DXT Extension
Overview
Ollama Deep Researcher is a Desktop Extension (DXT) that enables advanced topic research using web search and LLM synthesis, powered by a local MCP server. It supports configurable research parameters, status tracking, and resource access, and is designed for seamless integration with the DXT ecosystem.
- Research any topic using web search APIs and LLMs (Ollama, DeepSeek, etc.)
- Configure max research loops, LLM model, and search API
- Track status of ongoing research
- Access research results as resources via MCP protocol
Features
- Implements the MCP protocol over stdio for local, secure operation
- Defensive programming: error handling, timeouts, and validation
- Logging and debugging via stderr
- Compatible with DXT host environments
Directory Structure
.
├── manifest.json # DXT manifest (see MANIFEST.md for spec)
├── src/
│ ├── index.ts # MCP server entrypoint (Node.js, stdio transport)
│ └── assistant/ # Python research logic
│ └── run_research.py
├── README.md # This documentation
└── ...
Installation & Setup
- Clone the repository and install dependencies:
git clone <your-repo-url>
cd mcp-server-ollama-deep-researcher
npm install
- Install Python dependencies for the assistant:
cd src/assistant
pip install -r requirements.txt
# or use pyproject.toml/uv if preferred
- Set required environment variables for web search APIs:
- For Tavily:
TAVILY_API_KEY - For Perplexity:
PERPLEXITY_API_KEY - Example:
export TAVILY_API_KEY=your_tavily_key
export PERPLEXITY_API_KEY=your_perplexity_key
- Build the TypeScript server (if needed):
- Run the extension locally for testing:
node dist/index.js
# Or use the DXT host to load the extension per DXT documentation
Usage
- Research a topic:
- Use the
research tool with { "topic": "Your subject" }
- Get research status:
- Configure research parameters:
- Use the
configure tool with any of: maxLoops, llmModel, searchApi
Manifest
See manifest.json for the full DXT manifest, including tool schemas and resource templates. Follows DXT MANIFEST.md.
Logging & Debugging
- All server logs and errors are output to
stderr for debugging. - Research subprocesses are killed after 5 minutes to prevent hangs.
- Invalid requests and configuration errors return clear, structured error messages.
Security & Best Practices
- All tool schemas are validated before execution.
- API keys are required for web search APIs and are never logged.
- MCP protocol is used over stdio for local, secure communication.
Testing & Validation
- Validate the extension by loading it in a DXT-compatible host.
- Ensure all tool calls return valid, structured JSON responses.
- Check that the manifest loads and the extension registers as a DXT.
Troubleshooting
- Missing API key: Ensure
TAVILY_API_KEY or PERPLEXITY_API_KEY is set in your environment. - Python errors: Check Python dependencies and logs in
stderr. - Timeouts: Research subprocesses are limited to 5 minutes.
References
© 2025 Your Name or Organization. Licensed under MIT.