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clumsynonono

Aave Liquidation MCP Server

by clumsynonono

get_user_positions

Retrieve detailed breakdown of user collateral and debt positions across all Aave V3 assets to analyze position health and identify liquidation opportunities.

Instructions

Get detailed breakdown of a user collateral and debt positions across all Aave V3 assets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesEthereum address to query

Implementation Reference

  • src/index.ts:81-95 (registration)
    Registration of the 'get_user_positions' tool in the MCP server's listTools handler, including name, description, and input schema.
    {
      name: 'get_user_positions',
      description:
        'Get detailed breakdown of a user collateral and debt positions across all Aave V3 assets.',
      inputSchema: {
        type: 'object',
        properties: {
          address: {
            type: 'string',
            description: 'Ethereum address to query',
          },
        },
        required: ['address'],
      },
    },
  • MCP server handler for 'get_user_positions' tool: validates input, calls AaveClient.getUserReserves, and formats response as JSON.
    case 'get_user_positions': {
      const address = args?.address as string;
      if (!address || typeof address !== 'string') {
        throw new McpError(
          ErrorCode.InvalidParams,
          'address parameter is required and must be a string'
        );
      }
    
      if (!aaveClient.isValidAddress(address)) {
        throw new McpError(
          ErrorCode.InvalidParams,
          'Invalid Ethereum address format'
        );
      }
    
      const positions = await aaveClient.getUserReserves(address);
    
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(
              {
                address,
                collateralPositions: positions.collateral,
                debtPositions: positions.debt,
              },
              null,
              2
            ),
          },
        ],
      };
    }
  • Core implementation of get_user_positions: fetches all reserves, queries user reserve data in parallel, categorizes into collateral and debt positions with formatted values.
    async getUserReserves(userAddress: string): Promise<{
      collateral: UserReserveData[];
      debt: UserReserveData[];
    }> {
      const reserves = await this.getAllReserves();
      const collateral: UserReserveData[] = [];
      const debt: UserReserveData[] = [];
    
      // Parallel query all user reserves
      const userReservePromises = reserves.map(reserve =>
        this.dataProviderContract.getUserReserveData(reserve.tokenAddress, userAddress)
      );
      const userReservesData = await Promise.all(userReservePromises);
    
      // Process results
      for (let i = 0; i < reserves.length; i++) {
        const reserve = reserves[i];
        const userReserve = userReservesData[i];
        const totalDebt = userReserve.currentStableDebt + userReserve.currentVariableDebt;
    
        if (userReserve.currentATokenBalance > 0n || totalDebt > 0n) {
          // Use cached decimals from reserves
          const decimals = reserve.decimals;
    
          const data: UserReserveData = {
            asset: reserve.tokenAddress,
            symbol: reserve.symbol,
            currentATokenBalance: userReserve.currentATokenBalance,
            currentStableDebt: userReserve.currentStableDebt,
            currentVariableDebt: userReserve.currentVariableDebt,
            usageAsCollateralEnabled: userReserve.usageAsCollateralEnabled,
            decimals,
            balanceFormatted: ethers.formatUnits(userReserve.currentATokenBalance, decimals),
            debtFormatted: ethers.formatUnits(totalDebt, decimals),
            liquidationBonus: reserve.liquidationBonus,
          };
    
          if (userReserve.currentATokenBalance > 0n) {
            collateral.push(data);
          }
          if (totalDebt > 0n) {
            debt.push(data);
          }
        }
      }
    
      return { collateral, debt };
    }
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 of behavioral disclosure. It states the tool retrieves data ('Get detailed breakdown'), implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns real-time or cached data, or handles errors. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and scope, making it easy to parse quickly. Every part of the sentence earns its place by specifying key details.

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 the tool's complexity (querying financial positions across assets), lack of annotations, and no output schema, the description is minimally adequate. It covers the purpose but misses behavioral traits, usage context, and return value details. For a tool with no structured support, it should do more to compensate, but it meets the basic threshold.

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

Parameters3/5

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

The input schema has 100% description coverage, with the 'address' parameter clearly documented as an 'Ethereum address to query'. The description adds no additional parameter details beyond what the schema provides, such as format examples or validation rules. Baseline 3 is appropriate since the schema does the heavy lifting.

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's purpose with a specific verb ('Get') and resource ('user collateral and debt positions'), specifying the scope ('across all Aave V3 assets'). It distinguishes from siblings like 'get_user_health' by focusing on detailed breakdowns rather than health metrics, but doesn't explicitly differentiate from all siblings like 'batch_check_addresses'.

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 prerequisites, exclusions, or compare with siblings like 'get_user_health' for health-focused queries or 'batch_check_addresses' for multiple addresses. Usage is implied by the purpose but lacks explicit context.

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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