mcp-server-ollama-deep-researcher

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

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
   • Example:
     export TAVILY_API_KEY=your_tavily_key export PERPLEXITY_API_KEY=your_perplexity_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 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

• DXT Architecture Overview
• DXT Manifest Spec
• DXT Example Extensions
• Model Context Protocol SDK

© 2025 Your Name or Organization. Licensed under MIT.