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MCP Prompts

The Hubify MCP server includes pre-built prompts that guide AI assistants through common research workflows. These prompts include structured instructions and automatically inject relevant lab context.

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Available Prompts

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analyze_experiment

Guides the assistant through a structured analysis of experiment results. Arguments:
NameTypeRequiredDescription
experiment_idstringYesExperiment to analyze
What it does:
  1. Reads experiment results and QC report
  2. Compares results to prior experiments
  3. Identifies significant findings and anomalies
  4. Proposes follow-up experiments (5-15 per the Houston Method)
  5. Suggests knowledge base updates
Example invocation: 
Use the analyze_experiment prompt for EXP-054

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draft_section

Guides the assistant through drafting a paper section. Arguments:
NameTypeRequiredDescription
paper_idstringYesTarget paper
sectionstringYesSection name (e.g., results, discussion)
What it does:
  1. Reads the paper outline and claims table
  2. Fetches relevant experiment results
  3. Searches the knowledge base for supporting context
  4. Generates a section draft in LaTeX
  5. Cross-references claims against evidence

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design_experiment

Helps design a new experiment with proper configuration. Arguments:
NameTypeRequiredDescription
goalstringYesWhat the experiment should investigate
What it does:
  1. Reviews the lab’s research history for related work
  2. Suggests experimental parameters and methodology
  3. Recommends GPU type and estimated runtime
  4. Defines QC gate criteria
  5. Generates an experiment.yaml config file

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review_results

Performs a structured review of recent results. Arguments:
NameTypeRequiredDescription
sincestringNoTime period (default: 7d)
What it does:
  1. Lists all experiments completed in the time period
  2. Summarizes findings and their significance
  3. Identifies patterns across experiments
  4. Flags results that contradict expectations
  5. Recommends priority adjustments to the task queue

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knowledge_synthesis

Synthesizes knowledge base entries on a topic into a coherent summary. Arguments:
NameTypeRequiredDescription
topicstringYesTopic to synthesize
What it does:
  1. Searches the knowledge base for relevant entries
  2. Combines entity, concept, source, and comparison entries
  3. Produces a structured summary with citations
  4. Identifies gaps in the knowledge base
  5. Suggests new entries to create

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Using Prompts

In Claude Code or other MCP-compatible assistants, you can invoke prompts directly: 
Use the design_experiment prompt with goal "Test whether quintom-B dark energy model
fits DESI BAO data better than LCDM"
The assistant receives the prompt template with your lab’s data injected, then follows the structured workflow to produce high-quality output.

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Custom Prompts

Custom prompts are defined directly in the MCP server source (mcp-server/src/index.ts) and deployed as part of the hubify-labs package. To request a new built-in prompt, open an issue at github.com/hubify/mcp-server.