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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
PROJECT_PATHYesPath to your analysis directory where results are saved. Set in the env of the MCP server configuration.

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
analyze_bioinformatics_taskB

Analyze user intent and create a bioinformatics workflow plan. This tool helps understand your analysis goals and prepares the workflow structure. After this, ask Claude to generate Python scripts (≤100 lines each), then use execute_claude_script to run them.

debug_workflowC

Analyze workflow execution results and provide debugging insights

execute_claude_scriptA

🚀 MAIN TOOL: Automatically detect and execute Python scripts generated by Claude LLM for bioinformatics tasks. Features: ✅ Auto-detects Python installation ✅ Provides detailed installation guide if Python missing ✅ Auto-installs required packages (pandas, numpy, biopython, etc.) ✅ Full execution logging and error handling ✅ Script length monitoring (recommends ≤100 lines) ✅ HTML report generation with auto-browser opening

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.6/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: planning analysis (analyze_bioinformatics_task), executing scripts (execute_claude_script), and debugging (debug_workflow). No functional overlap.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., analyze_bioinformatics_task, debug_workflow, execute_claude_script), making them predictable.

Tool Count5/5

With only 3 tools, the set is well-scoped for its bioinformatics workflow automation purpose—each tool is essential and not excessive.

Completeness4/5

The tools cover planning, execution, and debugging—the core workflow. Minor gap: no explicit data retrieval or result analysis tool, but execution report generation partially addresses this.

Maintenance

ActivityInactive
ResponsivenessNo issues