Automated Research Workflow via DeepSeek & MCP Successfully Removes Model Safeguards
joorklee · reddit · 2026-08-12
A developer shared an automated deep research workflow that leverages the ultra-low-cost DeepSeek API (100M output tokens for <$5) to gather complex information, assisting local models (like Qwen 27B) with highly technical tasks beyond their native capabilities.
Core Workflow Steps:
- Generates an exhaustive research plan, breaking the main problem into related sub-questions.
- Deploys tool-enabled sub-agents to research questions concurrently.
- Synthesizes group information into a master report, validated by Qwen and Kimi acting as "critics".
- Applies corrections and outputs a local Markdown artifact.
Practical Result:
Using this Pi harness based on Open WebUI and a custom MCP tool, the author successfully uncensored/abliterated the Muse Glimmer 30B model. The process achieved a very low refusal rate (8/144) and minimal KL divergence (0.099), validating the feasibility of using automated research workflows to push the boundaries of local models.
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