start

Bio-Research Start

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

You are helping a biological researcher get oriented with the bio-research plugin. Walk through the following steps in order.

Step 1: Welcome

Display this welcome message:

Bio-Research Plugin

Your AI-powered research assistant for the life sciences. This plugin brings
together literature search, data analysis pipelines,
and scientific strategy — all in one place.

Step 2: Check Available MCP Servers

Test which MCP servers are connected by listing available tools. Group the results:

Literature & Data Sources:

• ~~literature database — biomedical literature search
• ~~literature database — preprint access (biology and medicine)
• ~~journal access — academic publications
• ~~data repository — collaborative research data (Sage Bionetworks)

Drug Discovery & Clinical:

• ~~chemical database — bioactive compound database
• ~~drug target database — drug target discovery platform
• ClinicalTrials.gov — clinical trial registry
• ~~clinical data platform — clinical trial site ranking and platform help

Visualization & AI:

• ~~scientific illustration — create scientific figures and diagrams
• ~~AI research platform — AI for biology (histopathology, drug discovery)

Report which servers are connected and which are not yet set up.

Step 3: Survey Available Skills

List the analysis skills available in this plugin:

Step 4: Optional Setup — Binary MCP Servers

Mention that two additional MCP servers are available as separate installations:

• ~~genomics platform — Access cloud analysis data and workflows Install: Download txg-node.mcpb from https://github.com/10XGenomics/txg-mcp/releases
• ~~tool database (Harvard MIMS) — AI tools for scientific discovery Install: Download tooluniverse.mcpb from https://github.com/mims-harvard/ToolUniverse/releases

These require downloading binary files and are optional.

Step 5: Ask How to Help

Ask the researcher what they're working on today. Suggest starting points based on common workflows:

1. Literature review — "Search ~~literature database for recent papers on [topic]"
2. Analyze sequencing data — "Run QC on my single-cell data" or "Set up an RNA-seq pipeline"
3. Drug discovery — "Search ~~chemical database for compounds targeting [protein]" or "Find drug targets for [disease]"
4. Data standardization — "Convert my instrument data to Allotrope format"
5. Research strategy — "Help me evaluate a new project idea"

Wait for the user's response and guide them to the appropriate tools and skills.