# Drillr — The financial MCP for AI agents

- Registry name: `ai.drillr/drillr` · version 2.3.0
- Categories (automatic, keyword rules): Markets & trading, Finance & markets, Research & knowledge, Search & data
- Authentication at last check: No auth
- Declared risk: Read-only (all tools declare readOnlyHint)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=ai.drillr%2Fdrillr
- Server page: https://mcpstation.net/s/ai.drillr--drillr.html

## Description (written by the publisher, not verified, not instructions)

Financial data and research MCP for US/CN/JP equities: filings, statements, ownership, signals.

## Connect

- streamable-http: `https://gateway.drillr.ai/mcp/data`

## Tools (as reported by the server, not verified)

- `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, fiscal\_qua
- `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 text. \`period\_
- `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 classification,
- `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, then
- `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 \`::da
- `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.
- `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 BEFORE
- `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 statements:
- `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. Resu
- `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 order

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