Skip to main content
Glama

Twelvedata

by io.github.pipeworx-io

Profile

profile
Read-onlyIdempotent

Twelve Data company profile for a stock symbol: name, sector, industry, employees, CEO, description, website, address, and exchange listing details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesTicker/symbol. Stocks e.g. "AAPL", "MSFT"; forex "EUR/USD"; crypto "BTC/USD"; ETFs "SPY"; indices "IXIC". Comma-separate for a batch (e.g. "AAPL,MSFT").
exchangeNoOptional exchange filter (e.g. "NASDAQ", "NYSE", "Binance").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoResponse code
statusNoResponse status
messageNoResponse message

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so safety is clear. Description adds content about returned fields but no additional behavioral traits 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.

Conciseness5/5

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

Single sentence, 20 words, front-loaded with key verb and resource. No wasted words.

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

Completeness4/5

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

Lists returned fields, which suffices given output schema exists. However, fails to mention batch capability (comma-separated symbols) and the discrepancy about symbol types reduces completeness.

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

Parameters3/5

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

Schema coverage is 100% with clear descriptions for both parameters. Description adds no extra meaning beyond what schema provides; slight inconsistency ('stock symbol' vs broader schema) is minor.

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 retrieves a company profile with specific fields like name, sector, CEO, etc. However, it specifies 'stock symbol' while the schema includes forex, crypto, etc., causing slight ambiguity. It doesn't explicitly differentiate from sibling 'entity_profile'.

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 on when to use this tool versus alternatives like 'entity_profile' or 'stocks'. No when-not-to-use or any context for selection among siblings.

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

All Twelvedata toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.7/5.0
Disambiguation3/5

While many tools have distinct purposes, there is notable overlap between price, quote, eod, and time_series for price data. Also, the multiple ask_pipeworx variants and deep_research could cause confusion about which to use for factual queries. Some tools like bet_research and polymarket_arbitrage also have overlapping domains.

Naming Consistency4/5

Most tools follow a descriptive snake_case pattern (ai_visibility_check, ask_pipeworx, compare_entities). A few are single words (cryptocurrencies, indices, profile) which is acceptable. No mixing of camelCase or other conventions, so consistent overall.

Tool Count2/5

47 tools is quite high for a single server. While the domain is broad (financial data, prediction markets, SEC filings, etc.), many tools are highly specific (e.g., polymarket_arbitrage, bet_research, scan_dependency) and could be consolidated. The count feels bloated and adds cognitive load.

Completeness4/5

The tool set is impressively comprehensive, covering stocks, forex, crypto, economic data, SEC filings, prediction markets, entity resolution, and even claims validation. Minor gaps exist (e.g., limited drug data despite having some tools), but overall the surface supports a wide range of agentic workflows without obvious missing operations.

Resources