Skip to main content
Glama
0xReisearch

REI Crypto MCP Server

by 0xReisearch

get_yield_pools

Retrieve comprehensive yield pool data with predictions to analyze DeFi investment opportunities.

Instructions

GET /yields/pools

Retrieve the latest data for all pools, including enriched information such as predictions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'get_yield_pools' MCP tool. Decorated with @mcp.tool() for registration, it fetches the latest yield pools data from the DefiLlama API endpoint '/yields/pools' and returns it as a string.
    @mcp.tool()
    async def get_yield_pools() -> str:
        """GET /yields/pools
        
        Retrieve the latest data for all pools, including enriched information such as predictions.
        """
        result = await make_request('GET', '/yields/pools')
        return str(result)
  • Helper function used by get_yield_pools and other tools to perform HTTP requests to the DefiLlama API.
    async def make_request(method: str, endpoint: str, params: Optional[Dict[str, Any]] = None) -> Any:
        """Make a request to the DefiLlama API."""
        try:
            response = await client.request(method, endpoint, params=params)
            response.raise_for_status()
            return response.json()
        except Exception as e:
            return f"Error: {str(e)}"
  • Initialization of the FastMCP server instance where tools like get_yield_pools are registered via decorators.
    mcp = FastMCP("defillama")
  • Entry point that runs the MCP server, making all registered tools available.
    if __name__ == "__main__":
        mcp.run(transport='stdio') 
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions retrieving 'latest data' and 'enriched information such as predictions,' which hints at read-only behavior and data freshness, but doesn't explicitly state whether this is a read operation, if it requires authentication, rate limits, or what the response format entails. For a tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded, consisting of just two sentences that efficiently convey the purpose and scope. Every word earns its place, with no redundant or unnecessary information, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is reasonably complete. It specifies the resource (pools), data recency (latest), and enrichment (predictions), which provides good context. However, with no annotations, it could better address behavioral aspects like read-only nature or response format, though the output schema mitigates some of this.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter details, and it correctly implies no filtering or arguments are required by stating it retrieves data for 'all pools.' This aligns well with the schema, earning a baseline 4 for zero-parameter tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves latest data for all pools with enriched information like predictions. It specifies the verb (retrieve), resource (pools), and scope (all pools with enriched data). However, it doesn't explicitly differentiate from sibling tools like get_yield_pools_borrow or get_yield_pools_old, which would require a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like get_yield_pools_borrow or get_yield_pools_old, nor does it specify any context or prerequisites for usage. This leaves the agent without direction on tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/0xReisearch/crypto-mcp-beta'

If you have feedback or need assistance with the MCP directory API, please join our Discord server