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NARAVINDR321

Financial Analysis MCP Server

by NARAVINDR321

mcp_plot_price_chart

Visualize OHLCV data with customizable price charts, including line and candlestick options. Generate, save, and analyze financial trends for trading research and investment insights.

Instructions

Generates a price chart (line or candlestick) from OHLCV data. 
Args:
    prices: List of dicts with keys 'date', 'open', 'high', 'low', 'close', 'volume'.
    chart_type: 'line' or 'candlestick'.
    title: Chart title.
    filename: Optional filename to save the plot.
Returns:
    Dict with 'file_path' and 'base64' of the image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chart_typeNoline
filenameNo
pricesYes
titleNoPrice Chart
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool generates and optionally saves a chart, but lacks critical details such as required permissions, file format (e.g., PNG, JPEG), whether it overwrites existing files, error handling, or performance characteristics like rate limits. This is inadequate for a tool that creates files.

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 efficiently structured with a purpose statement followed by bullet-like sections for Args and Returns, using minimal sentences that each add value. It avoids redundancy and is appropriately sized for the tool's complexity, making it easy to scan and understand.

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

Completeness3/5

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

Given no annotations and no output schema, the description partially meets contextual needs. It explains parameters well and specifies the return format, but lacks behavioral details like file handling or error conditions. For a chart-generation tool with file output, more context on operational aspects would improve completeness.

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?

The description adds significant meaning beyond the input schema, which has 0% description coverage. It clearly defines the 'prices' parameter structure (list of dicts with specific keys), explains 'chart_type' options ('line' or 'candlestick'), and notes that 'filename' is optional for saving. This fully compensates for the schema's lack of documentation.

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's purpose with specific verbs ('generates a price chart') and resources ('from OHLCV data'), distinguishing it from siblings like mcp_plot_comparison_chart or mcp_plot_financial_metric by focusing on price data visualization. It explicitly mentions chart types (line or candlestick), making the scope unambiguous.

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?

The description provides no guidance on when to use this tool versus alternatives. With siblings like mcp_plot_comparison_chart and mcp_plot_financial_metric, there is no indication of when price charting is preferred over other visualization tools, nor any mention of prerequisites or typical use cases.

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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