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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OPENAI_API_KEYNoYour OpenAI API key required for content generation
YOUTUBE_API_KEYNoOptional YouTube API key for enhanced functionality

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
set_api_keysD
check_api_keysD
extract_transcriptD
summarize_transcriptD
generate_linkedin_postD
youtube_to_linkedin_postD

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

D1.9/5.0

Scored across 6 tools

Disambiguation4/5

Most tools have distinct purposes: checking/setting API keys, extracting/summarizing transcripts, generating posts, and a combined YouTube-to-post workflow. However, 'generate_linkedin_post' and 'youtube_to_linkedin_post' could cause some confusion about when to use each, as the latter might implicitly include extraction and summarization steps.

Naming Consistency4/5

Tool names follow a consistent snake_case pattern with clear verb-action structures (e.g., 'check_api_keys', 'extract_transcript'). The only minor deviation is 'youtube_to_linkedin_post', which uses a 'source_to_destination' format instead of a verb-noun style, but it remains readable and fits the overall convention.

Tool Count5/5

With 6 tools, this server is well-scoped for its purpose of generating LinkedIn posts from various inputs. Each tool appears to serve a specific function in the workflow, from API management to content processing and post generation, without being overly sparse or bloated.

Completeness3/5

The toolset covers key steps like API setup, content extraction, summarization, and post generation, but there are notable gaps. For example, there's no tool for editing or updating existing posts, managing drafts, or handling post scheduling, which could limit agent workflows in a complete LinkedIn posting lifecycle.

Maintenance

ActivityInactive
ResponsivenessUnresponsive