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drasticstatic

hummingbot-mcp

by drasticstatic
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

search_history

Retrieve historical order, perpetual position, and CLMM position data from the database for analysis, reporting, and tax purposes. Filter by account, connector, trading pair, status, time range, and more.

Instructions

Search historical data from the backend database.

This tool is for historical analysis, reporting, and tax purposes.
For real-time current state, use get_portfolio_overview() instead.

Data Types:
- orders: Historical order data (filled, cancelled, failed)
- perp_positions: Perpetual positions (both open and closed)
- clmm_positions: CLMM LP positions (both open and closed)

Common Filters (apply to all data types):
    account_names: Filter by account names (optional)
    connector_names: Filter by connector names (optional)
    trading_pairs: Filter by trading pairs (optional)
    status: Filter by status (optional, e.g., 'OPEN', 'CLOSED', 'FILLED', 'CANCELED')
    start_time: Start timestamp in seconds (optional)
    end_time: End timestamp in seconds (optional)
    limit: Maximum number of results (default: 50, max: 1000)
    offset: Pagination offset (default: 0)

CLMM-Specific Filters:
    network: Network filter for CLMM positions (optional)
    wallet_address: Wallet address filter for CLMM positions (optional)
    position_addresses: Specific position addresses for CLMM (optional)

Examples:
- Search filled orders: search_history("orders", status="FILLED", limit=100)
- Search closed perp positions: search_history("perp_positions", status="CLOSED")
- Search all CLMM positions: search_history("clmm_positions", limit=100)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
data_typeYes
account_namesNo
connector_namesNo
trading_pairsNo
statusNo
start_timeNo
end_timeNo
limitNo
offsetNo
networkNo
wallet_addressNo
position_addressesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

A4.3/5.0
Behavior3/5

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

No annotations provided, so description must disclose behavior. It implies read-only nature but does not explicitly state lack of side effects, rate limits, or permissions. Some context is given but not comprehensive.

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?

Description is structured into sections with clear headings and examples. It is reasonably concise given the number of parameters, though slightly verbose in places.

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 no output schema and no annotations, the description provides sufficient context for an agent to select and invoke the tool. It covers data types, filters, and usage examples, though return format and errors are omitted.

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?

Schema coverage is 0%, but description compensates by listing and explaining each parameter with context, including examples and default values. However, some parameters (e.g., account_names) are less detailed.

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 searches historical data and lists three specific data types. It also distinguishes from sibling tool get_portfolio_overview by noting it is for real-time data.

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

Usage Guidelines5/5

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

Explicitly advises using get_portfolio_overview for real-time queries instead. Provides detailed information on data types and filters, guiding appropriate usage.

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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