MCP DeFiLlama Airdrops
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_airdropsB | Buscar todos os airdrops disponíveis no DeFiLlama |
| filter_airdropsC | Filtrar airdrops por critérios específicos |
| get_best_airdropsC | Obter os melhores airdrops baseado em critérios de valor e facilidade |
| debug_scraperC | Debugar o scraper para verificar se está funcionando corretamente |
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 4 tools
The tools are mostly distinct: get_airdrops retrieves all airdrops, get_best_airdrops filters for top ones, and filter_airdrops allows custom filtering. However, get_best_airdrops and filter_airdrops could be confused since both involve filtering, though their descriptions clarify one is preset criteria and the other is user-defined.
All tool names follow a consistent verb_noun pattern with snake_case: debug_scraper, filter_airdrops, get_airdrops, and get_best_airdrops. The verbs (debug, filter, get) are clear and appropriately matched to their actions.
With 4 tools, the count is borderline thin for a DeFiLlama airdrops server, as it might lack operations like detailed airdrop info, subscription, or status updates. However, it covers core retrieval and filtering functions adequately.
The server provides basic read and filter operations but has notable gaps: no create, update, or delete tools for managing airdrops, and no tools for user actions like claiming or tracking airdrops. It focuses on retrieval and filtering, which may limit agent workflows.