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RSS3-Network

RSS3 MCP Server

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by RSS3-Network

API-getStakerProfitSnapshots

Retrieve profit snapshots for stakers to track earnings and performance over time using RSS3 network data.

Instructions

Retrieve snapshots of the staker profit

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Generic handler for executing all dynamically generated API tools, such as API-getStakerProfitSnapshots. It looks up the corresponding OpenAPI operation by tool name, invokes the HTTP client to execute it with the provided parameters, and returns the JSON response or structured error.
    // handle tool calling
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
    	// console.error("call tool", request.params);
    	const { name, arguments: params } = request.params;
    
    	console.error("name", name);
    
    	if (name === "API-get-input-schema") {
    		for (const mcpToolWithClient of mcpToolWithClients) {
    			for (const [toolName, def] of Object.entries(
    				mcpToolWithClient.mcpTools.tools,
    			)) {
    				for (const method of def.methods) {
    					const toolNameWithMethod = `${toolName}-${method.name}`;
    					const truncatedToolName = toolNameWithMethod.slice(0, 64);
    					if (truncatedToolName === params.toolName) {
    						return {
    							content: [
    								{ type: "text", text: JSON.stringify(method.inputSchema) },
    							],
    						};
    					}
    				}
    			}
    		}
    		throw new Error(`Method ${params.toolName} not found`);
    	}
    
    	// find operation
    	const mcpToolWithClient = mcpToolWithClients.find(
    		(t) => t.mcpTools.openApiLookup[name],
    	);
    	if (!mcpToolWithClient) {
    		throw new Error(`Method ${name} not found`);
    	}
    
    	const operation = mcpToolWithClient.mcpTools.openApiLookup[name];
    
    	// execute
    	try {
    		const response = await mcpToolWithClient.client.executeOperation(
    			operation,
    			params,
    		);
    		return {
    			content: [
    				{
    					type: "text", // currently this is the only type that seems to be used by mcp server
    					text: JSON.stringify(response.data), // TODO: pass through the http status code text?
    				},
    			],
    		};
    	} catch (error) {
    		console.error("Error in tool call", error);
    		if (error instanceof HttpClientError) {
    			console.error(
    				"HttpClientError encountered, returning structured error",
    				error,
    			);
    			const data = error.data?.response?.data ?? error.data ?? {};
    			return {
    				content: [
    					{
    						type: "text",
    						text: JSON.stringify({
    							status: "error", // TODO: get this from http status code?
    							...(typeof data === "object" ? data : { data: data }),
    						}),
    					},
    				],
    			};
    		}
    		throw error;
    	}
    });
  • index.js:99-147 (registration)
    Dynamic registration of API tools via the ListToolsRequestHandler. Iterates over OpenAPI-derived MCP tools to construct tool names as `${toolName}-${method.name}` (truncated), descriptions, and generic input schemas. Includes the special API-get-input-schema tool. This is where API-getStakerProfitSnapshots would be registered if present in the OpenAPI specs.
    // handle tool listing
    server.setRequestHandler(ListToolsRequestSchema, async () => {
    	console.error("list tools");
    	/**
    	 * @typedef {import("@modelcontextprotocol/sdk/types.js").Tool} Tool
    	 * @type {Tool[]}
    	 */
    	const tools = [];
    
    	for (const mcpToolWithClient of mcpToolWithClients) {
    		for (const [toolName, def] of Object.entries(
    			mcpToolWithClient.mcpTools.tools,
    		)) {
    			for (const method of def.methods) {
    				console.error("method", method);
    				const toolNameWithMethod = `${toolName}-${method.name}`;
    				const truncatedToolName = toolNameWithMethod.slice(0, 64);
    				const trimmedDescription = method.description.split("Error")[0].trim();
    				tools.push({
    					name: truncatedToolName,
    					description: trimmedDescription,
    					inputSchema: {
    						type: "object",
    						properties: {},
    					},
    				});
    			}
    		}
    	}
    
    	tools.unshift({
    		name: "API-get-input-schema",
    		description:
    			"Get the input schema for a given API. We should always use this tool to get the input schema for a given API before calling the API.",
    		inputSchema: {
    			type: "object",
    			properties: {
    				toolName: {
    					type: "string",
    					description: "The name of the tool to get the input schema for",
    				},
    			},
    		},
    	});
    
    	console.error("tools", tools);
    
    	return { tools };
    });
  • Helper that converts OpenAPI specs to MCP tools using OpenAPIToMCPConverter.convertToMCPTools(), creating the mcpTools objects used for lookup and execution of individual API tools like API-getStakerProfitSnapshots.
    const mcpToolWithClients = converterWithClients.map((cwc) => {
    	const mcpTools = cwc.converter.convertToMCPTools();
    	return {
    		mcpTools,
    		client: cwc.client,
    	};
    });
  • Helper that initializes OpenAPIToMCPConverter and HttpClient instances from fetched RSS3 OpenAPI specifications.
    const converterWithClients = openApiSpecs.map((o) => {
    	const converter = new OpenAPIToMCPConverter(o.spec);
    	return {
    		converter,
    		client: o.client,
    	};
    });
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the action ('retrieve') but doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, pagination, or what format the snapshots are in (e.g., time-series data). This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by conveying essential information without redundancy.

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

Completeness2/5

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

Given the tool's complexity (likely involving data retrieval with potential behavioral nuances), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'snapshots' entail (e.g., historical data points, time ranges, or aggregation), the return format, or any prerequisites, leaving the agent with insufficient context for effective use.

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, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied as it meets the requirement for a parameterless tool.

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 'Retrieve snapshots of the staker profit' clearly states the verb ('retrieve') and resource ('snapshots of the staker profit'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'getStakerProfit' (which might fetch current profit vs. historical snapshots) or 'getStakerProfitSnapshots' (which appears identical), leaving some ambiguity about its specific scope.

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. For example, it doesn't specify if this is for historical data versus real-time data, or how it differs from 'getStakerProfit' or other snapshot-related tools in the sibling list, leaving the agent without context for selection.

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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