This server provides access to financial stock data via the Alpha Vantage API. You can:
Retrieve current stock quotes using the getStockQuote tool by providing a stock symbol
Fetch historical stock data with the getHistoricalData tool, allowing customization of the time interval (daily, weekly, monthly) and output size (compact, full)
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@findata-mcp-server get the current stock price for Apple"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
This is an MCP server that provides access to the Alpha Vantage API, allowing stock data retrieval to be used as context to LLMs.
getStockQuote: Get the current quote for a stock.
getHistoricalData: Get historical data for a stock (daily, weekly, or monthly).
(More tools will be added later for technical analysis, company overview, etc.)
Related MCP server: AlphaVantage MCP Server
To install Financial Data Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install findata-mcp-server --client claudenpm install findata-mcp-serverObtain an API key from Alpha Vantage https://www.alphavantage.co/support/#api-key.
Configure your MCP client (e.g., Claude Desktop) to connect to the server:
{
"mcpServers": {
"alphaVantage": {
"command": "npx",
"args": ["-y", "findata-mcp-server"],
"env": {
"ALPHA_VANTAGE_API_KEY": "PUT_YOUR_API_KEY_HERE"
}
}
}
}getStockQuoteGet the current quote for a stock.
Input:
symbol: The stock symbol (e.g., AAPL)
Output Example:
getHistoricalDataGet historical data for a stock.
Input:
symbol: the stock symbol (e.g., AAPL)
interval: the time interval for the data (daily, weekly, or monthly) (optional, default: daily)
outputsize: the size of the output (compact or full) (optional, default: compact)
Output:
JSON object containing the historical data. The structure of the output depends on the interval parameter.
Contributions are welcome! Please open an issue or pull request.
MIT
Get historical data for a stock.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | The stock symbol (e.g., AAPL) | |
| interval | No | The time interval for the data (daily, weekly, or monthly) | daily |
| outputsize | No | The size of the output (compact or full) | compact |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention any traits such as rate limits, data source reliability, or what happens with out-of-range dates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but fails to front-load key information or structure context. It is not overly verbose, but some additional structuring would improve usability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three parameters and no output schema, the description is too minimal. It does not explain return format, pagination, or data coverage, leaving the agent without necessary context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides for each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves historical stock data, which is distinct from the sibling getStockQuote. The verb 'Get' and resource 'historical data for a stock' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 (e.g., getStockQuote). There is no mention of use cases, prerequisites, or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the current quote for a stock.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | The stock symbol (e.g., AAPL) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is too brief, lacking details about the data returned (e.g., price, change, volume) or any behavioral constraints like rate limits or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no unnecessary words, achieving maximum conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, no output schema), the description is adequate but missing details about what the quote includes, which would help the agent understand the return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the symbol parameter fully, and the tool description adds no additional meaning beyond that, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Get) and resource (current quote for a stock), and the name distinguishes it from the sibling tool getHistoricalData.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for current data versus historical data from the sibling, but it does not explicitly state when to use this tool or when not to.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.1getHistoricalDatagetStockQuoteThe two tools are clearly distinct: one retrieves historical data and the other retrieves the current quote, with no overlap in functionality.
Both tools follow a consistent verb_noun naming pattern (getHistoricalData, getStockQuote), making them predictable and easy to understand.
With only two tools, the server feels too sparse for a comprehensive financial data API, lacking common operations like search, bulk queries, or parameterized requests.
The tool set is severely incomplete for a financial data server, missing essential functionality such as querying multiple stocks, specifying date ranges, or obtaining metadata, leading to likely dead ends for agents.
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If you are the server author, to access and configure the admin panel.
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