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Glama
Fadi88

LLM Inference Pricing Research Server

by Fadi88
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
ANTHROPIC_API_KEYYesYour Anthropic API key
FIRECRAWL_API_KEYYesYour Firecrawl API key

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
scrape_websitesB
Scrape multiple websites using Firecrawl and store their content.

Args:
    websites: Dictionary of provider_name -> URL mappings
    formats: List of formats to scrape ['markdown', 'html'] (default: both)
    api_key: Firecrawl API key (if None, expects environment variable)
    
Returns:
    List of provider names for successfully scraped websites
extract_scraped_infoC
Extract information about a scraped website.

Args:
    identifier: The provider name, full URL, or domain to look for
    
Returns:
    Formatted JSON string with the scraped information

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.1/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: 'scrape_websites' performs the scraping operation to gather data, while 'extract_scraped_info' retrieves and formats previously scraped information. There is no overlap in functionality - one creates data, the other queries it.

Naming Consistency4/5

Both tools use snake_case naming which is consistent, but they follow different verb patterns: 'scrape_websites' uses a verb_noun format while 'extract_scraped_info' uses verb_adjective_noun. This minor deviation prevents a perfect score, but the naming is still clear and readable.

Tool Count2/5

With only 2 tools for a 'LLM Inference Pricing Research Server', the surface feels severely underpowered. The server's name suggests comprehensive pricing research capabilities, but the tools only cover basic website scraping and data extraction - missing essential operations like price comparison, model benchmarking, cost analysis, or API integration that would be expected for this domain.

Completeness2/5

The toolset is severely incomplete for the stated purpose of 'LLM Inference Pricing Research'. While scraping and extraction are useful first steps, there are no tools for analyzing pricing data, comparing providers, calculating costs, or generating research reports. The server provides only data collection capabilities without the analysis tools needed to fulfill its research purpose.

Maintenance

ActivityStale
ResponsivenessNo issues

Resources