FinBridge

Technical Indicators (FinBridge DB)

get_technicals

Read-only

Latest technical-indicator snapshot for a single KR or US company from the local finbridge database (indicators_latest, refreshed by the nightly 'indicators' ingest from daily prices), plus an optional on-demand historical series and a plain-language signal summary.

Indicators: SMA 5/20/60/120, EMA 12/26, RSI(14, Wilder), MACD(12,26,9), Bollinger(20,2), ATR(14), 52-week high/low and % distance, returns over 1/5/20/60/120/250 trading days, 20-day volume ratio, above-SMA20/60 flags, and SMA20xSMA60 golden/dead cross (within the last 3 sessions).

Args:

company: US ticker (e.g. 'AAPL'), KR 6-digit stock code (e.g. '005930'), or company name. Resolution: exact ticker > 6-digit code > exact name > partial name.
history: 0-250 (default 0). 0 = latest snapshot only; >0 recomputes the last N sessions of close/sma20/sma60/rsi14/macd on the fly (not stored).
response_format: 'markdown' (default) or 'json'.

Returns: {company:{name,source,ticker|stock_code}, as_of, indicators:{...all snapshot fields...}, signals:[text], history:[{date,close,sma20,sma60,rsi14,macd}], notes}.

Examples:

{company: 'AAPL'} -> Apple's latest snapshot + signal summary
{company: '005930', history: 60} -> Samsung Electronics snapshot + last 60 sessions of sma/rsi/macd

Use when: reading one company's momentum/trend/overbought-oversold state, or charting an indicator series. Don't use to rank many companies (use screen_technical) or for live intraday quotes (use the live-source tools). Notes: KR/US/TW prices are adjusted for corporate actions but not dividends (indicators around dividend events may be slightly distorted); US history starts 2023-03-28 (volume from 2024-07-01) so long-window figures are shallower there. Market data, not investment advice. Errors: unknown company -> no-match/candidate-list error; 'No technical snapshot' -> no indicator row for this company, with a market-specific reason (JP/EU carry no prices; new listing or delisted elsewhere).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`company`	Yes	US ticker (e.g. 'AAPL'), KR 6-digit stock code (e.g. '005930'), or company name
`history`	No	0 = latest snapshot only; 1-250 = also return that many recent sessions of close/sma20/sma60/rsi14/macd
`response_format`	No	'markdown' for tables, 'json' for compact machine-readable output	markdown

Output Schema

TableJSON Schema

Name	Required	Description	Default
`as_of`	No
`notes`	No
`company`	Yes
`history`	No
`signals`	No
`indicators`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A5/5.0

Behavior5/5

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

Annotations only declare readOnlyHint and openWorldHint; the description goes far beyond by explaining data origin and refresh cadence (nightly ingest), on-demand recomputation not stored, corporate-action adjustment caveats, US history start dates, and expected error cases. These behaviors materially affect interpretation of returned data.

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 long but appropriately so for a tool with many indicators and caveats. The core purpose is front-loaded, and the headed sections (Indicators, Args, Returns, Examples, Use when, Notes, Errors) are dense with actionable information. No sentence is filler.

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

Completeness5/5

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

For a complex tool, this description covers everything needed to call it correctly: parameters, return shape, examples, alternatives, error modes, data caveats, and market-data disclaimer. An agent can confidently decide to invoke it and interpret results from the description alone.

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?

Schema coverage is 100%, but the description adds meaning beyond the schema: company resolution order (exact ticker > 6-digit code > exact name > partial name), the exact recompute behavior of history, and the response_format effect. These details are not present in the input schema alone.

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?

States a specific verb and resource: fetching the latest technical-indicator snapshot for a single KR or US company. It enumerates the indicators covered, distinguishes single-company scope from screening tools, and the title/name are not merely restated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use the tool ('reading one company's momentum/trend/overbought-oversold state, or charting an indicator series') and when not to ('Don't use to rank many companies (use screen_technical) or for live intraday quotes (use the live-source tools)'). It names sibling tools and gives exclusion conditions.

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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TDQS

A4.2/5.0

Disambiguation4/5

Most tools have clearly distinct resource+action targets, and the overlapping screen_* tools are thoroughly cross-referenced with 'use screen_X instead' guidance. Minor ambiguity exists between get_disclosure_feed, get_dart_filings, and get_dart_major_events, which all surface KR filings from different angles but remain distinguishable.

Naming Consistency5/5

Every tool follows a consistent verb_noun snake_case pattern: get_* for retrievers, screen_* for screeners, search_* for lookups, plus action verbs like analyze_, backtest_, compare_, import_, and query_. Subfamilies (dart_*, edgar_*, fred_*, crypto_*) are consistently prefixed, making tool selection predictable.

Tool Count3/5

37 tools is heavy, and the four momentum screeners (canslim/kell/minervini/schwartz) plus three KR disclosure tools could arguably be collapsed into parameterized variants. However, the server's unusually broad scope—KR/US/TW/JP/EU equities, crypto, macro, portfolio, backtesting—means most tools earn their place, so the count is high but not chaotic.

Completeness4/5

The surface covers the core workflow well: search, prices, fundamentals, filings, insider trades, valuation, screeners, backtesting, and portfolio tracking for KR/US, plus crypto and macro. Notable gaps are the lack of single-company financial-statement tools for TW/JP/EU (only available through screen_companies) and no real-time stock quotes, but these are workable for the stated local-database research purpose.

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