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drasticstatic

hummingbot-mcp

by drasticstatic
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Python
Hybrid

get_portfolio_overview

Get a unified overview of your cryptocurrency portfolio: token balances, perpetual positions, LP positions, and active orders across exchanges. Filter by account or connector, and include only the sections you need.

Instructions

Get a unified portfolio overview with balances, perpetual positions, LP positions, and active orders.

This tool provides a comprehensive view of your entire portfolio by fetching data from multiple sources
in parallel. By default, it returns all four types of data, but you can filter to only include
specific sections.

Data Sources (fetched in parallel using asyncio.gather):
1. Token Balances - Holdings across all connected CEX/DEX exchanges
2. Perpetual Positions - Open perpetual futures positions from CEX
3. LP Positions (CLMM) - Real-time concentrated liquidity positions from blockchain DEXs
   - Queries database to find all pools user has interacted with
   - Calls get_positions() for each pool to fetch real-time blockchain data
   - Includes real-time fees and token amounts
4. Active Orders - Currently open orders across all exchanges

NOTE: This only shows ACTIVE/OPEN positions. For historical data, use search_history() instead.

Args:
    account_names: List of account names to filter by (optional). If empty, returns all accounts.
    connector_names: List of connector names to filter by (optional). If empty, returns all connectors.
    include_balances: Include token balances in the overview (default: True)
    include_perp_positions: Include perpetual positions in the overview (default: True)
    include_lp_positions: Include LP (CLMM) positions in the overview (default: True)
    include_active_orders: Include active (open) orders in the overview (default: True)
    as_distribution: Show token balances as distribution percentages (default: False)
    refresh: If True, refresh balances from exchanges before returning. If False, return cached state (default: True)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_namesNo
connector_namesNo
include_balancesNo
include_perp_positionsNo
include_lp_positionsNo
include_active_ordersNo
as_distributionNo
refreshNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses key behavioral traits: fetching data in parallel with asyncio.gather, querying multiple sources, database queries for LP positions, real-time data retrieval, and refresh vs cached behavior. This provides meaningful context beyond what annotations would convey.

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

Conciseness4/5

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

The description is moderately long but well-structured with a clear overview, data source list, and parameter section. Every sentence serves a purpose, though it could be slightly more concise by merging the data source list with the parameter descriptions. It remains informative without being verbose.

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 complexity (8 parameters, no output schema, no annotations), the description is highly complete. It explains the data sources, filtering options, refresh behavior, and historical data separation. The only minor gap is the lack of output format description, but this is acceptable without an output schema.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It does so excellently by explaining each parameter (account_names, connector_names, include_balances, etc.), their defaults, and their effects. For example, it clarifies that 'include_lp_positions' triggers database queries and real-time blockchain calls. This adds significant value beyond the raw schema.

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

Purpose5/5

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

The description clearly states the tool provides a 'unified portfolio overview' with specific data types (balances, perpetual positions, LP positions, active orders). It distinguishes itself from sibling tool search_history by noting this shows only active/open positions, while search_history handles historical data.

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

Usage Guidelines4/5

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

The description explains when to use the tool (for a comprehensive portfolio overview) and explicitly directs users to search_history for historical data. It also details filtering options like account_names and connector_names. However, it does not cover all sibling tools or provide a comprehensive decision tree.

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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