workflow-generator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_workflowA | Scan a project directory and generate WORKFLOW.html — a visual system workflow showing all components, their communication paths, concurrency model, concurrent request capacity, and bottleneck analysis. Works with Python (FastAPI, Flask, Django), Node.js (Express, Nest.js), Go, and mixed projects. Detects: API frameworks, gateways, LLM providers, vector stores, databases, queues, rate limits, async primitives, and worker counts. |
| analyze_workflowA | Scan a project and return the workflow analysis as structured JSON (no file written). Returns: framework, workers, capacity estimates, detected components (LLM, storage, queues, external sources), concurrency primitives (semaphores, rate limits), and bottleneck ranking. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
Both tools deal with workflow analysis, but they produce different outputs: analyze_workflow returns JSON, generate_workflow creates an HTML file. The descriptions make the distinction clear, though some conceptual overlap remains.
Both tool names follow a consistent verb_noun pattern with snake_case, making them predictable and easy to understand.
Only two tools for a 'workflow generator' server feels thin. The domain likely requires more operations (e.g., update, delete, validate) to be useful.
The server provides analysis and generation but lacks update, delete, or customization tools. Basic lifecycle coverage is missing, limiting agent workflows.