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REI Crypto MCP Server

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get_emission_data

Retrieve emission data for crypto protocols to analyze token distribution and supply metrics using the REI Crypto MCP Server.

Instructions

GET /api/emission/{protocol}

Unlocks data for a given token/protocol.

Parameters:
    protocol: protocol slug (e.g., 'aave')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
protocolYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'get_emission_data' tool. It is decorated with @mcp.tool() for registration and fetches emission data for the given protocol from the DefiLlama API using the shared make_request helper.
    @mcp.tool()
    async def get_emission_data(protocol: str) -> str:
        """GET /api/emission/{protocol}
        
        Unlocks data for a given token/protocol.
        
        Parameters:
            protocol: protocol slug (e.g., 'aave')
        """
        result = await make_request('GET', f'/api/emission/{protocol}')
        return str(result)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Unlocks data' but does not clarify if this is a read-only operation, requires authentication, has rate limits, or what the output entails (though an output schema exists). The term 'Unlocks' is vague and could imply mutative or computational behavior without further explanation.

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

Conciseness3/5

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

The description is brief but includes unnecessary technical details (e.g., 'GET /api/emission/{protocol}') that do not aid the AI agent. The core purpose and parameter explanation are front-loaded, but the structure could be more streamlined by omitting the API endpoint and focusing solely on functional guidance.

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

Completeness3/5

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

Given 1 parameter with low schema coverage and an output schema present, the description provides basic parameter semantics but lacks details on behavioral traits, usage context, or output interpretation. It is minimally adequate for a simple data-fetching tool but misses opportunities to clarify scope or differentiate from siblings like 'get_emissions.'

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 description adds meaning by specifying that the 'protocol' parameter is a 'protocol slug' with an example ('aave'), which is valuable since the input schema has 0% description coverage and only provides a title. With 1 parameter, this compensates well, though it could further clarify allowed values or format constraints.

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

Purpose3/5

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

The description states 'Unlocks data for a given token/protocol,' which provides a vague purpose but lacks specificity about what type of data (e.g., emission rates, schedules, metrics) or what 'unlocks' means operationally. It distinguishes from siblings by focusing on emission data, but the verb 'Unlocks' is ambiguous compared to clearer alternatives like 'Retrieves' or 'Fetches.'

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?

No guidance is provided on when to use this tool versus alternatives, such as sibling tools like 'get_emissions' (which might overlap) or other data-fetching tools. The description does not mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the tool name alone.

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

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