Skip to main content
Glama
deenesjakoruzh
Rekko-AI

Rekko MCP

by Rekko-AI
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

get_calibration

Retrieve signal accuracy metrics including Brier scores, hit rates, and total signals to assess prediction calibration for trading decisions.

Instructions

Get signal accuracy and calibration metrics — Brier score, hit rates, total signals.

Args: category: Filter by category (e.g. "crypto", "politics") or "" for all. period: Time period: "7d", "30d", "90d", or "all". mode: Trading mode: "shadow" or "live".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNo
periodNoall
modeNoshadow

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • src/rekko_mcp/server.py:180-193 (handler)
    The get_calibration function is registered as an MCP tool and handles the retrieval of signal accuracy and calibration metrics from the Rekko API.
    async def get_calibration(
    category: str = "", period: str = "all", mode: str = "shadow"
) -> str:
    """Get signal accuracy and calibration metrics — Brier score, hit rates, total signals.

    Args:
        category: Filter by category (e.g. "crypto", "politics") or "" for all.
        period: Time period: "7d", "30d", "90d", or "all".
        mode: Trading mode: "shadow" or "live".
    """
    params: dict = {"period": period, "mode": mode}
    if category:
        params["category"] = category
    return await _request("GET", "/v1/calibration", params=params)

Tool Definition Quality

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries full burden. It successfully discloses what metrics are returned (Brier score, hit rates, total signals), but omits operational details like read-only safety, rate limits, or caching behavior that would help an agent understand invocation constraints.

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?

Efficiently structured with the purpose front-loaded in the first sentence, followed by a clear Args section. No redundant text; every sentence earns its place.

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 presence of an output schema, the description appropriately omits detailed return value explanations. All parameters are documented. Minor gap: doesn't explicitly state this is a safe read-only operation, though implied by the verb 'Get'.

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?

Despite 0% schema description coverage, the Args section comprehensively documents all 3 parameters with examples (e.g., 'crypto', 'politics') and valid values (e.g., '7d', '30d', 'shadow', 'live'), fully compensating for the schema deficiency.

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?

Clearly states it retrieves 'signal accuracy and calibration metrics' with specific examples (Brier score, hit rates). The mention of Brier score helps distinguish it from sibling tools like get_performance or get_analysis, though it doesn't explicitly contrast with 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?

Provides no guidance on when to use this versus get_performance or get_analysis, nor when to prefer 'shadow' vs 'live' mode. No prerequisites or exclusion criteria are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Rekko-AI/rekko-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server