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 (Tavily, Perplexity, Exa) 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

Related MCP server: MCP Ollama Server

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

Installation & Setup

1. Clone the repository and install dependencies:

   git clone <your-repo-url> cd mcp-server-ollama-deep-researcher npm install

2. Install Python dependencies for the assistant:

   cd src/assistant pip install -r requirements.txt # or use pyproject.toml/uv if preferred

3. Set required environment variables for web search APIs:

   • For Tavily: TAVILY_API_KEY

   • For Perplexity: PERPLEXITY_API_KEY

   • For Exa: EXA_API_KEY (Get yours at https://dashboard.exa.ai/api-keys)

   • Example:

     export TAVILY_API_KEY=your_tavily_key export PERPLEXITY_API_KEY=your_perplexity_key export EXA_API_KEY=your_exa_key

4. Build the TypeScript server (if needed):

   npm run build

5. 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:

  • Use the get_status tool

• 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, PERPLEXITY_API_KEY, or EXA_API_KEY is set in your environment depending on which search API you're using.

• Python errors: Check Python dependencies and logs in stderr.

• Timeouts: Research subprocesses are limited to 5 minutes.

Search API Comparison

• Tavily: Fast, comprehensive web search with raw content extraction

• Perplexity: AI-powered search with natural language summaries and citations

• Exa: Neural search engine optimized for semantic search with highlights

References

• DXT Architecture Overview

• DXT Manifest Spec

• DXT Example Extensions

• Model Context Protocol SDK