# Drillr — The financial MCP for AI agents (remote · gateway.drillr.ai)

The financial MCP for AI agents - 90+ financial tables, SEC filings, signals, alt-data.

- Trust score: 76/100 (medium)
- Change this week: +9
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-04

## Components

- remote · `gateway.drillr.ai`: 76/100 (this document), [markdown](https://verifymcp.io/servers/ai-drillr-drillr/mcp-data.md), [page](https://verifymcp.io/servers/ai-drillr-drillr/mcp-data)

## Channel facts

- Endpoint: `https://gateway.drillr.ai/mcp/data`
- Transports: `streamable-http`
- Auth: `required`
- Version: `2.1.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-04.

- **Endpoint Security**: 89/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation is enforced on tool calls, advertised via RFC 9728 protected-resource metadata. Discovery is public, which costs nothing: no tool can be invoked without a token.
  - HTTPS is enforced; there's no plaintext access path.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
  - The authorisation server offers only Dynamic Client Registration (RFC 7591), which MCP 2026-07-28 deprecated in favour of Client ID Metadata Documents.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 58/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 3006 tokens (~334/item across 9 items; 9 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 30/100
  - Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 96/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 89% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http ai-drillr-drillr https://gateway.drillr.ai/mcp/data
```

### Codex

```toml
[mcp_servers.ai-drillr-drillr]
url = "https://gateway.drillr.ai/mcp/data"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-drillr-drillr": {
      "type": "remote",
      "url": "https://gateway.drillr.ai/mcp/data",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add ai-drillr-drillr --url https://gateway.drillr.ai/mcp/data --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  ai-drillr-drillr:
    url: "https://gateway.drillr.ai/mcp/data"
```

### Other

```json
{
  "mcpServers": {
    "ai-drillr-drillr": {
      "type": "http",
      "url": "https://gateway.drillr.ai/mcp/data"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-04 (score 76, +1)

- [security] Tool “run_sql” rewrote its description, which is the text the model reads
- [functional] Schema quality: good → excellent

### 2026-08-03 (score 75, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-01 (score 74, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 73, +5)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-29 (score 67, 0)

- [security] The server rewrote its instructions, which are the text every model session reads
- [security] Tool “list_tables” rewrote its description, which is the text the model reads
- [cosmetic] “list_tables” reworded the description of “categories”
- [cosmetic] “list_tables” made “categories” optional

### 2026-07-28 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 66, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

## MCP tools (9)

### `sec_report_list` (~265 tokens)

Use to discover which SEC filings exist for a ticker before searching content.
For the actual content use sec_report_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_quarter, filing_type, filing_date, period_start, period_end).

filing_types filter: omit for main reports only (US 10-K/10-Q/20-F/S-1/DEF 14A
\+ /A amendments; JP 120/140/160; HK/A-share annual_report / quarterly_report /
q1_report; excludes ad-hoc 8-K/6-K); pass [] for all indexed types; pass explicit
allowlist to override.

Input parameters:

- `filing_types` (array): Filter by filing type. Omit for default (periodic reports + IPO/shelf registrations + amendments; excludes ad-hoc disclosures). Pass [] for all indexed types. Pass an explicit allowlist to override —…
- `ticker` (string, required): Stock ticker, e.g. NVDA, 6758.T, 00700.HK, 600519.SH

### `sec_report_search` (~558 tokens)

Use when you need narrative content from company filings — risk factors, MD&A, guidance language, deal terms, accounting policies, share structure. For consolidated financial numbers use run_sql on financial_statements instead.

Semantic search over the full text of company-filed reports; returns matching passages.

Coverage: US + Japan + Hong Kong + China A-shares. US = SEC EDGAR (including foreign issuers' 20-F/6-K). Japan = EDINET, `.T` ticker (6758.T). Hong Kong = HKEX filings, 5-digit `.HK` ticker (00700.HK). A-shares = `.SH`/`.SZ` (600519.SH, 300750.SZ).

Parameters:
\- query (required): natural-language search; phrase it as the concept or section name you want, e.g. "share repurchase authorization", "Risk Factors". Run a few phrasings rather than one broad query.
\- ticker (required): US bare (NVDA), Japan `.T`, HK `.HK`, A-share `.SH`/`.SZ`, ADRs as their US symbol (SONY).
\- filing_types (optional): US = SEC form names (10-K, 10-Q, 8-K, 20-F, 6-K, DEF 14A, S-1/F-1, + amendments). Japan = EDINET NUMERIC codes: 120 (annual), 140 (quarterly), 160 (semi-annual). HK/A-share = plain names — annual_report; A-share quarters per-quarter (q1_report, ...); HK quarterly results all quarterly_report. OMIT to search all types.
\- period_start / period_end (optional): yyyy-mm window; omit to search all history.
\- top_k (optional): max passages to return (default 10).

Scope: indexes ONLY company-filed reports — NOT institutional filings (13F-HR/13D/13G; for those use insider_and_institution_activities with source='institution').

Section targets: non-GAAP reconciliations → earnings 8-K (Ex 99.1); dilution / SBC / buyback → "Shareholders' Equity"; segment breakdown → "Segment Information"; guidance → "Outlook" in MD&A; exec comp → DEF 14A.

Input parameters:

- `filing_types` (array)
- `period_end` (string): End period YYYY-MM
- `period_start` (string): Start period YYYY-MM
- `query` (string, required): Search query
- `ticker` (string, required): Stock ticker, e.g. NVDA, 6758.T, 00700.HK, 600519.SH
- `top_k` (integer)

### `company_search` (~234 tokens)

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 base — searchable across industry classification, product offerings, business model, segment structure, competitive landscape, supply chain, management background, and customer profile.

Coverage: US, Japan, Hong Kong, and China A-shares. `market` accepts one lowercase value or a list from `us | jp | hk | cn`; omit it or pass `[]` for all four. List order does not set priority.

Pass a natural-language description (for example, "Hong Kong and China EV battery suppliers"). Returns a structured list of matching companies with context snippets.

ONLY for finding a LIST of companies by description.

Input parameters:

- `market`: Optional market filter. Pass one lowercase value or a list from 'us' | 'jp' | 'hk' | 'cn'. Omit or pass [] for all four; list order does not set priority.
- `query` (string, required): Natural-language company description

### `ticker_lookup` (~225 tokens)

Resolve a company name, brand, or ticker substring to canonical ticker(s). Use this FIRST when the user mentions a company by name/brand/nickname before running any ticker-keyed tool.

Input:
\- query (required): company name, brand, or ticker substring, e.g. "Apple", "苹果", "AAPL", "OpenAI"
\- market (optional): "us" | "jp" | "hk" | "cn" — omit to search all markets

Returns up to 5 matches ranked by prefix-hit first, then name length. Returned
symbols carry their market suffix: US bare (AAPL), Japan `.T`, Hong Kong 5-digit
\`.HK` (00700.HK), A-share `.SH`/`.SZ` (600519.SH).

Input parameters:

- `market` (string): Optional market filter: 'us' | 'jp' | 'hk' | 'cn'. Omit to search all markets.
- `query` (string, required): Company name or ticker substring (case-insensitive). Matches historical names + tickers too.

### `run_sql` (~398 tokens)

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 `::date` cast on it fails.
\- Filter structured tables by ticker (`WHERE ticker IN ('AAPL','MSFT')`; screening: add `ticker NOT LIKE '%-%'` to drop preferred stock).

Core equity coverage: US, Japan, Hong Kong, and China A-shares. Tickers are US bare (AAPL), Japan `.T` (6758.T), Hong Kong `.HK` (00700.HK), and A-shares `.SH`/`.SZ` (600519.SH, 300750.SZ). financial_statements, company_snapshot, and price_volume_history span all four. Specialized tables vary — call get_table_schema before treating an empty result as a finding.

Tables by domain (call get_table_schema for detail):
\- Market: price_volume_history (OHLCV history; MUST filter ticker + time_frame), index_price, equity_extended_rt (pre/after/overnight quotes)
\- Fundamentals: financial_statements (GAAP income/balance/cashflow), company_snapshot (ratios, per-share, growth)
\- Earnings: earning_call_summary, earning_call_calendar
\- Analyst: analyst_ratings, analyst_ratings_consensus
\- Ownership: insider_and_institution_activities
\- 8-K events: executive_change, company_deal_events, debt_issuance, securities_offering
\- Executives: executive_profile, executive_compensation
\- Alt-data: macro / industry / trade / AI-supply-chain — call list_tables(categories=[...])

Input parameters:

- `sql` (string, required): PostgreSQL SELECT query

### `get_table_schema` (~46 tokens)

Use BEFORE run_sql when you're unsure which columns a table has.

Look up column definitions (name, type, description) for a data table.

Input parameters:

- `table_name` (string, required)

### `fiscal_utility` (~187 tokens)

Use to convert between fiscal year/quarter and calendar months for a ticker before filtering period_end columns.

Coverage warning: fiscal-year configuration is primarily US, with sparse JP/HK entries and no China A-share coverage in the verified dataset. Do not assume this tool supports a ticker merely because the core equity tables do.

Forward: ticker + fiscal_year + fiscal_quarter → period_start/period_end. Reverse: ticker + yyyy_mm → fiscal_year/fiscal_quarter.

Input parameters:

- `fiscal_quarter` (integer): Quarter 1-4, or 0 for full fiscal year (required for forward conversion)
- `fiscal_year` (integer): Fiscal year (required for forward conversion)
- `ticker` (string, required): Stock ticker. Coverage is primarily US; sparse JP/HK; no China A-share configuration.
- `yyyy_mm` (string): Calendar month yyyy-mm (required for reverse conversion)

### `list_tables` (~276 tokens)

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 run_sql when you want to explore alt-data — run_sql alone won't
tell you which tables exist.

Available categories:
\- Energy & Power — US power plants, electricity prices, regional hourly generation/demand
\- Data Centers — facilities, GPU clusters, cooling
\- Semiconductors — AI chip specs, sales, ownership, foundry revenue, customs trade
\- Compute Pricing — GPU rental, cloud VM spot/on-demand, instance specs
\- Model Development — model specs, benchmarks, AI companies, AI polling, LLM arena
\- Inference Economics — LLM API pricing across providers
\- Macro & Trade — UN Comtrade, US Census trade flows, FRED macro series
\- Prediction Markets — Polymarket and Kalshi events, markets, trades, daily aggregates
\- Critical Minerals — USGS mineral deposits, country supply, critical materials

Input parameters:

- `categories` (array): Altdata category names (see tool description for the list). Omit, or pass "all", for the category index.

### `news_search` (~478 tokens)

Use for any news, event, development, or statement question about a company,
theme, or the market.

Covers US, Japan, Hong Kong and A-share markets; The `ticker` filter takes
exchange-suffixed symbols: US bare (AAPL), Japan `.T` (7203.T), Hong Kong
\`.HK` (00700.HK), A-share `.SH`/`.SZ` (600519.SH). 

Returns Markdown: a `## Stories` numbered list (each storyline once), then flat
\`## Events` and `## Claims` tables (claims = attributed statements: analyst
actions, corporate guidance, central-bank remarks). The Events `story` column
refers back to the Stories number. `sources` counts corroborating reports;
\`first_reported`/`last_reported` give the reporting span. Lowest-ranked stories
are dropped to fit length; the meta line flags how many were omitted.

At least one of query/theme/ticker/since/until is required. Per-parameter detail
is on the input schema — search_type=claims needs query/ticker/a time window,
not theme.

Input parameters:

- `order_by` (string): Result ordering. relevance (default) | event_time (newest event time first) | create_time (most recently ingested first).
- `query` (string): Semantic query (English). One of query/theme/ticker/since/until required.
- `search_type` (string): all (default) | events | claims (opinions/statements only).
- `since` (string): ISO8601; filter time_event >= since.
- `theme` (string): Theme word, resolved to the nearest canonical theme. Not valid with search_type=claims.
- `ticker`: Exact ticker symbol(s) — a single symbol, an array, or a comma-separated string; multiple tickers are an OR/overlap filter. US symbols bare (AAPL); other markets carry their exchange suffix — 7203.T,…
- `top_k` (integer): Story count. Default 10, max 50.
- `until` (string): ISO8601; filter time_event < until.

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/ai-drillr-drillr/mcp-data#diagnostics

## Score history

- 2026-08-04: 76
- 2026-08-03: 75
- 2026-08-02: 74
- 2026-08-01: 74
- 2026-07-31: 73
- 2026-07-30: 68
- 2026-07-29: 67
- 2026-07-28: 67
- 2026-07-27: 66
- 2026-07-26: 65

## Links

- Remote endpoint: https://gateway.drillr.ai/mcp/data
- Authorisation metadata: https://gateway.drillr.ai/.well-known/oauth-protected-resource/mcp/data
- Repository: https://github.com/Little-Grebe-Inc/drillr-mcp-server
- Website: https://drillr.ai/?ref=mp_registry
- Changelog RSS feed: https://verifymcp.io/servers/ai-drillr-drillr/mcp-data/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/ai-drillr-drillr/mcp-data/changelog.json
- HTML version of this page: https://verifymcp.io/servers/ai-drillr-drillr/mcp-data