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AlgoChains MCP Server

AlgoChains MCP Server

Official
by AlgoChains
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_bot_dashboard

Read-onlyIdempotent

Retrieve a real-time dashboard of live trading bots, showing PIDs, positions, today's P&L, signal counts, and win rates computed from actual fill history.

Instructions

Get real-time dashboard of all live trading bots: PIDs, positions, today's P&L, signal counts, win rates computed from actual fill history. Data from ~/.algochains/bot_metrics.db.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_bot_dashboard"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv22.7.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive. The description adds value by specifying the data source (~/.algochains/bot_metrics.db) and that win rates are computed from fill history, which are behavioral details beyond annotations.

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 exceptionally concise: two sentences covering purpose, data fields, and source. No filler or redundancy, fitting the critical information into minimal space.

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

Completeness5/5

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

Given no parameters and no output schema, the description fully informs the agent of the tool's return contents (PIDs, positions, P&L, signals, win rates) and data provenance. It is complete for the tool's low complexity and typical dashboard use case.

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 input schema has zero parameters with 100% coverage, so the baseline is 4. The description does not need to add parameter details, but it also does not mention any optional inputs that might be expected for a dashboard (e.g., date filter), which is acceptable given the explicit real-time nature.

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 it returns a real-time dashboard of all live trading bots with specific data fields. However, it does not distinguish itself from siblings like get_all_bot_metrics or get_live_bot_metrics, which may cause confusion for an agent choosing between them.

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. With many similar get_* tools for bot metrics, the absence of usage context or exclusions forces the agent to infer appropriateness, risking incorrect 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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