FinBridge

FinBridge DB Schema

get_db_schema

Read-only

Inspect the schema of the local finbridge database (SQLite with ingested KR/US company fundamentals, filings, and daily prices): tables, views, columns, per-table row counts (counted in the background and refreshed every 30 minutes; null with rows_note "counting…" right after a server start), and ready-to-run example queries for query_db.

Read this before writing a query_db statement. It returns no company data itself — get_db_schema describes the tables, query_db runs the SELECT.

Args: (none)

Returns: {tables: [{name, columns: [{name, type}], rows}], views: [{name, columns: [{name, type}]}], examples: [sql_string]}

Key objects:

companies: KR companies have source='dart' + stock_code (6-digit), US companies source='edgar' + ticker
financials: one row per company x fiscal_year x quarter (quarter=0 = annual); raw unscaled KRW/USD amounts
prices_daily: daily OHLCV per company_id
views v_financials (financials joined with company name/ticker/stock_code) and v_latest_annual (latest annual row per company) — prefer these in query_db

Examples:

Call before writing SQL for query_db, to learn table/column names.
Check row counts to see how much data the nightly ingest has loaded.

Use when: preparing a query_db, or checking ingest coverage. Don't use for market data itself (get_stock_prices / get_valuation / the screeners read the same tables with the right joins already done). FinBridge has no real-time equity quote tool — equity prices here are end-of-day closes from the nightly ingest; the only live data is crypto (get_crypto_ticker) and regulator filings (get_dart_filings / get_edgar_filings). Errors: 'database has not been built yet' — the ingest pipeline has not run on the server.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`views`	Yes
`tables`	Yes
`examples`	No
`rows_note`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 6, 2026
- addedOutput schema / properties / rows_note
```
Added value: +{
+  "type": "string"
+}
```
First observedSep 6, 2026

TDQS

A4.6/5.0

Behavior5/5

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

The description goes beyond the readOnlyHint annotation by explaining behavioral nuances: row counts are refreshed every 30 minutes, may show 'counting…' immediately after a server start, and that it returns no company data itself. It also discloses potential error messages and the meaning of 'database has not been built yet.'

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 long but well-organized, with clear sections for key objects, examples, usage, and errors. It front-loads the main purpose and provides essential context for the read-only nature. It is slightly verbose but all content is relevant and helpful.

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?

Given that the tool has no parameters, the description is very complete. It specifies the return structure, explains the key tables and views, gives example use cases, and lists error conditions. It fully prepares an agent to call the tool and interpret results.

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?

The tool has no parameters, and the schema declares an empty object, so there is nothing to clarify. The description explicitly states 'Args: (none)', which is redundant but harmless. Per the rubric, with high schema coverage and no parameters, a baseline score of 3 is appropriate.

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?

The description clearly states the tool inspects the schema of the local finbridge database, enumerating tables, views, columns, row counts, and example queries. It explicitly distinguishes itself from query_db by stating 'get_db_schema describes the tables, query_db runs the SELECT.'

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?

It provides explicit when-to-use guidance: 'Use when: preparing a query_db, or checking ingest coverage.' It also names what not to use it for and points to alternative tools like get_stock_prices and the screeners, which is excellent orientation.

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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