Analytics
drillr.ai
Provides access to SEC filings, company information, and financial data through search and SQL queries for analysis.
ENDPOINT 1
https://gateway.drillr.ai/mcp/data
MCP server metadata
- Name
- drillr-data
- Version
- 1.0.0
Drillr's data backend for global financial markets — direct, predictable, call-priced. Core equity coverage: US, Japan, and China A-shares. Ticker format: US bare (AAPL); Japan `.T` (6758.T); A-shares `.SH`/`.SZ` (600519.SH, 300750.SZ). Quote symbols containing "." or "^" in SQL. Specialized datasets can be narrower: earnings calls/calendar are US+JP; analyst, ownership, executive, 8-K events, and extended-hours are US-only. Call get_table_schema(table_name) before treating an empty result as a finding — every equity-scoped table states its coverage. Tools — pick the one that fits, then run_sql for anything custom: - list_tables / get_table_schema: discover tables; get one table's columns + coverage notes - run_sql: read-only SQL over the financial tables (list_tables/get_table_schema first) - company_search: find companies by natural-language description - ticker_lookup: resolve a name or ticker to its canonical symbol - filing_list: list a company's SEC filings - filing_search: search filings for structured as-reported facts (original and restated) plus the source text passages - industry_inflections: search cross-company industry inflection research (US) - ai_adoption: look up concrete enterprise AI applications from earnings-call disclosures (US) - news_search: semantic search over company and market news
Known tools 10
filing_listUse to discover which SEC filings exist for a ticker before searching content.
Inferred read-onlycompany_searchUse for qualitative company discovery (industry, business model, supply chain, competitors, management background).
Inferred read-onlyticker_lookupResolve a company name, brand, or ticker substring to canonical ticker(s).
Inferred read-onlyrun_sqlPostgreSQL SELECT over financial / market / alt-data tables — returns structured rows.
Inferred read-onlynews_searchUse for any news, event, development, or statement question about a company, theme, or the market.
Inferred read-onlyindustry_inflectionsSearch industry inflections identified through structured research of earnings calls held by US-listed companies after July 2026, including the change mechanism, impact scope, market attention and affected companies.
Inferred read-onlyai_adoptionSearch concrete enterprise AI applications disclosed in US company earnings calls from September 2023 to the present.
Inferred read-onlyCONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.drillr-data]
url = "https://gateway.drillr.ai/mcp/data"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"drillr-data": {
"type": "http",
"url": "https://gateway.drillr.ai/mcp/data"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: drillr-data
Remote MCP URL: https://gateway.drillr.ai/mcp/data
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"drillr-data": {
"url": "https://gateway.drillr.ai/mcp/data"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"drillr-data": {
"type": "http",
"url": "https://gateway.drillr.ai/mcp/data"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "drillr-data",
"transport": "streamable-http",
"url": "https://gateway.drillr.ai/mcp/data"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Trust Data Available
BuiltWith Trust API v2 evidence for drillr.ai was fetched 2026-07-29T11:10:23.867Z and is being refreshed.
drillr.ai is assessed as Trusted: Domain runs a meaningful technology spend, consistent with a real business.
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.