FinBrain MCP

analyst_ratings_by_ticker

Get normalized analyst ratings for any stock ticker, with rating history, signals, and price targets. Supports date filtering and JSON/CSV output.

Instructions

Normalized analyst ratings: { format: "json", ticker, name, series: [{date, rating_type, institution, signal, target_price_from, target_price_to, target_price_raw}, ...], series_count, series_total } CSV returns the sliced series.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "req": "<req>"
    },
    "name": "analyst_ratings_by_ticker"
  }
}

Input Schema

Name	Required	Description	Default
`req`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 29, 2026

TDQS

C2.6/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only shows the response structure but does not mention that the tool is read-only, any rate limits, side effects, or required permissions. The 'normalized' label hints at data processing but lacks explicit transparency.

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

Conciseness3/5

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

The description is fairly concise at a few lines but includes a verbose JSON structure that might clutter. It front-loads the concept of 'normalized analyst ratings' but then dumps details that could be in the output schema. Acceptable but not optimal.

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

Completeness2/5

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

Given the complexity (5 parameters, nested objects, no output schema) and 29 sibling tools, the description is insufficient. It does not explain the meaning of rating types, signals, or how CSV slice works. Missing details on pagination, defaults, or how to interpret the data, leaving gaps for an AI agent.

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

Parameters2/5

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

Schema coverage is 0% (no descriptions for most fields), so the description must compensate. It provides the output structure which indirectly explains the meaning of some parameters (e.g., date range via series), but does not describe the required 'ticker' parameter or the effect of 'limit' and 'format'. The output schema is missing, so the agent must infer parameter usage from the response example.

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 provides 'Normalized analyst ratings' and shows the expected JSON structure with fields like ticker, name, series, and rating details. This makes the primary function clear. However, it does not differentiate itself from sibling tools like 'recent_analyst_ratings' or 'screener_analyst_ratings', which slightly reduces clarity.

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 its many siblings. The description only mentions the output format without explaining the context or prerequisites (e.g., ticker is required). There is no mention of when not to use it or alternative tools.

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