FineData MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| FINEDATA_API_KEY | Yes | Your FineData API key | |
| FINEDATA_API_URL | No | API URL (default: https://api.finedata.ai) | https://api.finedata.ai |
| FINEDATA_TIMEOUT | No | Default timeout in seconds (default: 60) | 60 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| scrape_urlA | Scrape content from any web page with advanced antibot bypass. Features:
Use cases:
Token costs:
|
| scrape_asyncA | Submit an async scraping job for long-running requests. Use this for:
Returns a job_id that you can poll with get_job_status. |
| get_job_statusA | Get the status of an async scraping job. Statuses:
Poll this endpoint until status is 'completed' or 'failed'. |
| batch_scrapeA | Scrape multiple URLs in a single batch request. Benefits:
Returns a batch_id and list of job_ids for tracking. |
| get_usageB | Get current API usage and token statistics. Returns:
|
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose with no ambiguity: batch_scrape handles multiple URLs in parallel, scrape_async is for long-running single jobs, scrape_url is for immediate single requests with advanced features, get_job_status tracks async/batch jobs, and get_usage monitors API consumption. The descriptions explicitly differentiate use cases and workflows.
The naming follows a consistent snake_case pattern with clear verb_noun structures (e.g., batch_scrape, get_job_status, scrape_async). However, scrape_url deviates slightly by using a noun_verb format instead of a verb_noun pattern, which is a minor inconsistency in an otherwise predictable set.
With 5 tools, this server is well-scoped for web scraping operations. Each tool earns its place by covering distinct aspects of the workflow: submission (batch, async, immediate), status tracking, and usage monitoring. This count is neither too sparse nor bloated for the domain.
The tool surface provides complete coverage for the web scraping domain. It supports all key operations: multiple submission methods (batch, async, immediate), job lifecycle management (status tracking), and administrative functions (usage monitoring). There are no obvious gaps that would hinder agent workflows.