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Glama
andydukes
by andydukes

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

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

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
list_chatflowsA
List all available chatflows from the Flowise API.

This function respects optional whitelisting or blacklisting if configured
via FLOWISE_CHATFLOW_WHITELIST or FLOWISE_CHATFLOW_BLACKLIST.

Returns:
    str: A JSON-encoded string of filtered chatflows.
create_predictionA
Create a prediction by sending a question to a specific chatflow or assistant.

Args:
    chatflow_id (str, optional): The ID of the chatflow to use. Defaults to FLOWISE_CHATFLOW_ID.
    question (str): The question or prompt to send to the chatflow.

Returns:
    str: The raw JSON response from Flowise API or an error message if something goes wrong.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.5/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have completely distinct purposes: one lists available chatflows, and the other creates predictions using a specific chatflow. There is no overlap in functionality, and an agent can easily differentiate between them based on their clear descriptions.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern: list_chatflows and create_prediction. The naming is predictable and readable, with no deviations in style or convention across the tool set.

Tool Count2/5

With only 2 tools, the server feels thin for its apparent domain of interacting with Flowise chatflows. While the tools cover listing and creating predictions, the lack of operations like updating, deleting, or managing chatflows suggests an incomplete surface that may limit agent workflows.

Completeness2/5

The tool set is severely incomplete for a chatflow management domain. It only provides list and create operations, missing essential CRUD functionality such as updating or deleting chatflows, retrieving specific chatflow details, or handling prediction updates. This will likely cause agent failures in more complex scenarios.

Maintenance

ActivityInactive
ResponsivenessNo issues