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coreyjwang

FinDataMCP

by coreyjwang
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

FinDataMCP

To run:

  1. Clone repo

  2. Install uv (package manager):

    curl -LsSf https://astral.sh/uv/install.sh | sh

  3. Navigate to folder:

    cd FinDataMCP

  4. Install dependencies:

    # Create virtual env and activate it
uv venv
source .venv/bin/activate

# Install dependencies
uv add "mcp[cli]" httpx yfinance

  5. Check that everything's working by running server:

    uv run findata.py

Related MCP server: mysqldb-mcp-server

Connecting to Claude Desktop

  1. Install Claude Desktop if you haven't already

  2. Edit Claude Desktop configuration file (Claude>settings>developer>edit config):

  3. Add the following configuration:

    {
    "mcpServers": {
        "findata": {
            "command": "uv",
            "args": [
                "--directory",
                "/ABSOLUTE/PATH/TO/PARENT/FOLDER/FinDataMCP",
                "run",
                "findata.py"
            ]
        }
    }
}

  4. Restart Claude Desktop

For windows cmds: see https://modelcontextprotocol.io/quickstart/server

Available Tools

1 tool
get_stock_priceB

Get the current stock price using yfinance.

Args:
    symbol: Stock ticker (e.g. AAPL, TSLA, MSFT)
ParametersJSON Schema
NameRequiredDescriptionDefault
symbolYes

TDQS

B3/5.0
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. It mentions the data source (yfinance) but lacks critical behavioral details such as rate limits, error handling, freshness of data, or authentication requirements for a financial data tool.

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?

The description is appropriately sized and front-loaded with the core purpose, followed by parameter details. It avoids unnecessary fluff, though the formatting with 'Args:' could be slightly more polished.

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 no annotations, no output schema, and a single parameter, the description is incomplete. It lacks information on return values, error cases, and operational constraints, which are essential for effective tool use in an AI agent context.

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 description coverage is 0%, but the description compensates by explaining the 'symbol' parameter as 'Stock ticker' with examples (AAPL, TSLA, MSFT), adding meaningful context beyond the bare schema. However, it doesn't cover all potential nuances like format constraints.

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 the tool's purpose with a specific verb ('Get') and resource ('current stock price'), and mentions the data source ('using yfinance'). However, since there are no sibling tools, it cannot demonstrate differentiation from alternatives, preventing a perfect score.

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, prerequisites, or limitations. It only states what the tool does without context for usage decisions.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.0
    • First observedget_stock_price
Install Server
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TDQS

B3.1/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clear, distinct purpose focused on retrieving stock prices.

Naming Consistency5/5

The single tool name follows a clear verb_noun pattern (get_stock_price). With only one tool, consistency is inherently perfect as there are no other names to compare against.

Tool Count2/5

A single tool is too few for a server named 'FinDataMCP', which suggests a broader financial data domain. This minimal toolset severely limits functionality and does not align with the implied scope of financial data operations.

Completeness1/5

The tool surface is severely incomplete for a financial data server. It only provides stock price retrieval, missing essential operations like historical data, financial statements, market indices, currency rates, or any other common financial data queries.

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

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