bots.st/drillr-the-financial-mcp-for-ai-agents
Drillr — The financial MCP for AI agents
US/CN/JP equities filings and data research
1924 ms
answered our call
- State
- Answered
- Protocol
- MCP 2025-06-18
- Tools listed
- 10
- Answered
- 3 of the last 3 calls
How to reach it
- MCP, HTTP
https://gateway.drillr.ai/mcp/data
What it can do
| Tool | What it says it does |
|---|---|
ai_adoption | Search concrete enterprise AI applications disclosed in US company earnings calls. Filter by ticker, partially match a company name, search for an application or workflow by name, or use since in YYYY-MM-DD format to include only observations updated on or after that date. Returns a data array… |
company_search | Use for qualitative company discovery (industry, business model, supply chain, competitors, management background). For numerical screening (revenue, margins, ratios, growth rates) use run_sql on company_snapshot instead. Drillr's company knowledge graph — searchable across industry… |
filing_list | Use to discover which SEC filings exist for a ticker before searching content. For the actual content use filing_search instead. List indexed SEC filings for a given ticker with a summary header. Returns: summary (period coverage, per-type counts) + table of up to 50 filings (fiscal_year… |
filing_search | Search one company's SEC filings. Returns `## Facts` (exact as-reported and restated financial values) and `## Passages` (matching filing text) — both come back in one call. `ticker` is REQUIRED. When `## Facts` is empty, read `## Passages` — the figure is usually stated in the filing… |
get_table_schema | Column definitions (name, type, description) for a data table, plus its usage note where one exists: required filters, ticker format, and market coverage. |
industry_inflections | Search industry inflections identified through structured research of earnings calls held by US-listed companies, including the change mechanism, impact scope, market attention and affected companies. All filters are optional and combine with AND. With no filters, returns the newest first page… |
list_tables | List alternative-data tables under the given categories. Returns each table's name, one-line purpose, and column names (call get_table_schema if you need column types/comments). Batch up to 5 categories in one call; omit categories, or pass ["all"], to get the category index instead. Use this… |
news_search | Use for any news, event, development, or statement question about a company, theme, or the market. The `ticker` filter takes exchange-suffixed symbols. Returns Markdown: a `## Stories` numbered list (each storyline once), then flat `## Events` and `## Claims` tables (claims = attributed… |
run_sql | PostgreSQL SELECT over financial / market / alt-data tables — returns structured rows. Hard rules (query fails otherwise): - SELECT only, no CTE (`WITH ... AS`) — use subqueries. - Period columns are TEXT, not dates — `period_end` is 'YYYY-MM'. Compare as strings (`period_end >= '2024-01'`); a… |
ticker_lookup | Resolve a company name, brand, or ticker substring to canonical ticker(s). Input: - query (required): company name, brand, or ticker substring, e.g. "Apple", "AAPL", "OpenAI" - market (optional): "us" | "jp" | "cn" — omit to search all markets Returns up to 5 matches ranked by prefix-hit first… |
In its maker's words
Financial data and research MCP for US/CN/JP equities: filings, statements, ownership, signals.
- Website
- drillr.ai/docs/mcp?ref=mp_registry
- Source
- github.com/Little-Grebe-Inc/drillr-mcp-server
- Publisher
- drillr.ai
- Listed from
- the official MCP Registry as
ai.drillr/drillr - Version
- 2.3.0, updated 13 Sep 2026
- Kinds of work
- Finance and markets, Search and research, Data and databases
The domain it lives on
- drillr.ai
- registered 12 Mar 2026 (8 months ago), at GoDaddy.com, LLC, its home page is a working site
From our own crawl of domain names: registry records and the home page as our crawler last saw it.
Every call we made
| When | What happened | Time |
|---|---|---|
| Answered | 1924 ms | |
| Answered | 2345 ms | |
| Answered | 612 ms |
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