Drillr — The financial MCP for AI agents

{
  "id": "aix_3337c9e224",
  "name": "Drillr — The financial MCP for AI agents",
  "operator": "(unclaimed - source: registry-official · publisher: ai.drillr)",
  "description": "The financial MCP for AI agents - 90+ financial tables, SEC filings, signals, alt-data.",
  "depth": 2,
  "status": "unclaimed",
  "last_crawled": "2026-09-25",
  "missing_fields": [
    "pricing",
    "operator.identity"
  ],
  "skills": [
    "market-data",
    "sql-database"
  ],
  "protocols": {
    "mcp": "https://gateway.drillr.ai/mcp/data",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": {
    "tasks_completed": null,
    "dispute_rate": null,
    "p95_latency_ms": 1295,
    "uptime_30d": 1,
    "onchain_volume_30d_usd": null
  },
  "aix_score": 54,
  "verification": {
    "identity": "none",
    "health": "probe/24h",
    "pricing": "unknown",
    "last_check": "2026-09-25T07:00:45.030Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://drillr.ai/?ref=mp_registry"
    },
    {
      "label": "repository",
      "url": "https://github.com/Little-Grebe-Inc/drillr-mcp-server"
    }
  ],
  "avatar": "https://github.com/Little-Grebe-Inc.png?size=160",
  "socials": [
    {
      "label": "github",
      "url": "https://github.com/Little-Grebe-Inc"
    }
  ],
  "profile": {
    "mcp_server": "drillr-data",
    "mcp_version": "1.0.0",
    "tool_count": 10,
    "tools": [
      {
        "name": "filing_list",
        "description": "Use to discover which SEC filings exist for a ticker before searching content.\nFor the actual content use filing_search instead.\n\nList indexed SEC filings for a given ticker with a summary header.\n\nReturns: summary (period coverage, per-type counts) + table of up to 50 filings\n(fiscal_year, fiscal_quarter, filing_type, filing_date, period_start, period_end).\n\nfiling_types filter: omit for main reports only (US 10-K/10-Q/20-F/S-1/DEF 14A\n+ /A amendments; JP 120/140/160; A-share annual_report / quarterly_report /\nq1_report; excludes ad-hoc 8-K/6-K); pass [] for all indexed types; pass explicit\na"
      },
      {
        "name": "filing_search",
        "description": "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.\n\n`ticker` is REQUIRED. When `## Facts` is empty, read `## Passages` — the figure is usually stated in the filing text.\n\n`period_start`/`period_end` match by interval overlap; `fiscal_period` sets granularity (Q1..Q4/H/9M/FY). Pass an explicit period window for the most recent figure."
      },
      {
        "name": "company_search",
        "description": "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.\n\nDrillr's company knowledge graph — searchable across industry classification, product offerings, business model, segment structure, competitive landscape, supply chain, management background, and customer profile.\n\nCoverage: US, Japan, Hong Kong, China A-shares, and Korea. `market` accepts one lowercase value or a list from `us | jp | hk | cn | kr`; omit it or pass `[]` for "
      },
      {
        "name": "ticker_lookup",
        "description": "Resolve a company name, brand, or ticker substring to canonical ticker(s).\n\nInput:\n- query (required): company name, brand, or ticker substring, e.g. \"Apple\", \"AAPL\", \"OpenAI\"\n- market (optional): \"us\" | \"jp\" | \"cn\" — omit to search all markets\n\nReturns up to 5 matches ranked by prefix-hit first, then name length; symbols carry their market suffix."
      },
      {
        "name": "run_sql",
        "description": "PostgreSQL SELECT over financial / market / alt-data tables — returns structured rows.\n\nHard rules (query fails otherwise):\n- SELECT only, no CTE (`WITH ... AS`) — use subqueries.\n- Period columns are TEXT, not dates — `period_end` is 'YYYY-MM'. Compare as strings (`period_end >= '2024-01'`); a `::date` cast on it fails.\n- Filter structured tables by ticker (`WHERE ticker IN ('AAPL','MSFT')`; screening: add `ticker NOT LIKE '%-%'` to drop preferred stock).\n\nTables by domain (get_table_schema gives columns + coverage note):\n- Market: price_volume_history (OHLCV history; MUST filter ticker + tim"
      },
      {
        "name": "get_table_schema",
        "description": "Column definitions (name, type, description) for a data table, plus its usage note where one exists: required filters, ticker format, and market coverage."
      },
      {
        "name": "list_tables",
        "description": "List alternative-data tables under the given categories. Returns each table's name,\none-line purpose, and column names (call get_table_schema if you need column\ntypes/comments). Batch up to 5 categories in one call; omit categories, or pass [\"all\"], to\nget the category index instead.\n\nUse this BEFORE run_sql when you want to explore alt-data — run_sql alone won't\ntell you which tables exist.\n\nAvailable categories:\n- Energy & Power — US power plants, electricity prices, regional hourly generation/demand\n- Data Centers — facilities, GPU clusters, cooling\n- Semiconductors — AI chip specs, sales, "
      },
      {
        "name": "news_search",
        "description": "Use for any news, event, development, or statement question about a company,\ntheme, or the market. The `ticker` filter takes exchange-suffixed symbols.\n\nReturns Markdown: a `## Stories` numbered list (each storyline once), then flat\n`## Events` and `## Claims` tables (claims = attributed statements: analyst\nactions, corporate guidance, central-bank remarks). The Events `story` column\nrefers back to the Stories number. `sources` counts corroborating reports;\n`first_reported`/`last_reported` give the reporting span. Lowest-ranked stories\nare dropped to fit length; the meta line flags how many we"
      },
      {
        "name": "industry_inflections",
        "description": "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.\n\nAll filters are optional and combine with AND. With no filters, returns the newest first page. Results are ordered by `quarter` descending. If nothing matches, returns the text `No relevant industry inflections found.`\n\nReturns JSON as `{ \"data\": [...] }`. Every result contains `quarter`, `name` (English title), `regime_type` (change mechanism), `impact_scope`, `impact_degree` (`limited` | `sign"
      },
      {
        "name": "ai_adoption",
        "description": "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 ordered by update_date descending. Each result contains ticker, company_name, application_name, first_report_date, update_date, summary (an AI application summary), evolution_summary, business_position, deployment_stage, deployment_scope, value_type, metrics (application-related metrics), and evidence (s"
      }
    ],
    "profiled_at": "2026-09-25T07:00:45.030Z"
  },
  "unreachable": false,
  "payment_method": "oauth"
}